Many people associate prosthetic limbs with nude-colored imitations of human limbs. Something built to blend into a society where people have all of their limbs while serving functional use cases. On the other end of the spectrum are the highly optimized prosthetics used by Athletes, built for speed, low weight, and appearing nothing like a human limb.

As a child under 12 years old, neither of these categories of prosthetics particularly speaks to you. Open Bionics, founded by Joel Gibbard and Samantha Payne, was started to create a third category of prosthetics. One that targets the fun, imaginative side of children, while still providing the daily functional requirements.

Through partnerships with Disney and Lucasfilms, Open Bionics has built an array of imagination-capturing prosthetic limbs that are straight-up cool.

Joel Gibbard dives into why they founded Open Bionics, and why you should invest in their company as they are getting ready to let the general public invest in them for the first time.

Joel Gibbard

Joel Gibbard lives in Bristol, UK and graduated with a first-class honors degree in Robotics from the University of Plymouth, UK.

He co-founded Open Bionics alongside Samantha Payne with the goal of bringing advanced, accessible bionic arms to the market. Open Bionics offers the Hero Arm, which is available in the UK, USA, France, Australia, and New Zealand. Open Bionics is revolutionizing the prosthetics industry through its line of inspiration-capturing products.

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The first robots went into space over 60 years ago and robotics have become a familiar sight in many industrial settings, but it took a bit longer for robots to make their way into our homes. Robotic vacuum cleaners first started to make an appearance in homes about 20 years ago now, and according to a recent survey by the UK-RAS Network, 28% of people say that robots are now an occasional part of their everyday lives while 13% say they are fully integrated into their day to day lives. But home robots can do a lot more than clean the floors. Social and assistive robots can offer company and help around the home which can be game-changing for people with limited mobility or dementia.

In this special live recording for the UK Festival of Robotics, Claire chatted to Dr. Patrick Holthaus (University of Hertfordshire / Robot House), Prof. Praminda Caleb-Solly (University of Nottingham) and Dr Mike Aldred (Dyson).

Patrick Holthaus researches how robots can socially engage with humans letting them interact with each other in a special research facility, the Robot House at the University of Hertfordshire. He is particularly interested in non-verbal communication like body movements, gestures, and gaze and how they can influence the social credibility and trust of assistive and companion robots. At the same time, he maintains the robots and all the interactive technology in the house and coordinates and advises other users of the house as the Robot House manager.

Praminda Caleb-Solly is Professor of Embodied Intelligence at the University of Nottingham where she leads the Cyber-physical Health and Assistive Robotics Technologies research group. Prior to joining Nottingham, she led research in Assistive Robotics at the Bristol Robotics Laboratory for over ten years. In 2020 she co-founded Robotics for Good CIC, a ‘robots-as-a-service’ start-up which is currently supporting the deployment of telepresence robots.

Having gained a PhD in robotics from the University of Kent, Mike Aldred left in 1998 to be part of the original team of 5 roboticists at Dyson. He spent 15 years taking the company’s first robot vacuum cleaner from technology research right the way through to a manufactured product. He has worked on pretty much every area of domestic robotics from developing vision based navigation systems, to helping define international robot standards and ensuring the production line runs smoothly. The common theme running across all his roles at Dyson has been turning academic theory into practical reality.

Keywords: assistive, home, domestic, social, vacuum

Who wouldn’t want a robot to handle all the household drudgery? Skathi/iStock via Getty Images

By Ayonga Hereid (Assistant Professor of Mechanical and Aerospace Engineering, The Ohio State University)

With recent advances in artificial intelligence and robotics technology, there is growing interest in developing and marketing household robots capable of handling a variety of domestic chores.

Tesla is building a humanoid robot, which, according to CEO Elon Musk, could be used for cooking meals and helping elderly people. Amazon recently acquired iRobot, a prominent robotic vacuum manufacturer, and has been investing heavily in the technology through the Amazon Robotics program to expand robotics technology to the consumer market. In May 2022, Dyson, a company renowned for its power vacuum cleaners, announced that it plans to build the U.K.’s largest robotics center devoted to developing household robots that carry out daily domestic tasks in residential spaces.

Despite the growing interest, would-be customers may have to wait awhile for those robots to come on the market. While devices such as smart thermostats and security systems are widely used in homes today, the commercial use of household robots is still in its infancy.

As a robotics researcher, I know firsthand how household robots are considerably more difficult to build than smart digital devices or industrial robots.

Robots that can handle a variety of domestic chores are an age-old staple of science fiction.

Handling objects

One major difference between digital and robotic devices is that household robots need to manipulate objects through physical contact to carry out their tasks. They have to carry the plates, move the chairs and pick up dirty laundry and place it in the washer. These operations require the robot to be able to handle fragile, soft and sometimes heavy objects with irregular shapes.

The state-of-the-art AI and machine learning algorithms perform well in simulated environments. But contact with objects in the real world often trips them up. This happens because physical contact is often difficult to model and even harder to control. While a human can easily perform these tasks, there exist significant technical hurdles for household robots to reach human-level ability to handle objects.

Robots have difficulty in two aspects of manipulating objects: control and sensing. Many pick-and-place robot manipulators like those on assembly lines are equipped with a simple gripper or specialized tools dedicated only to certain tasks like grasping and carrying a particular part. They often struggle to manipulate objects with irregular shapes or elastic materials, especially because they lack the efficient force, or haptic, feedback humans are naturally endowed with. Building a general-purpose robot hand with flexible fingers is still technically challenging and expensive.

It is also worth mentioning that traditional robot manipulators require a stable platform to operate accurately, but the accuracy drops considerably when using them with platforms that move around, particularly on a variety of surfaces. Coordinating locomotion and manipulation in a mobile robot is an open problem in the robotics community that needs to be addressed before broadly capable household robots can make it onto the market.

A sophisticated robotic kitchen is already on the market, but it operates in a highly structured environment, meaning all of the objects it interacts with – cookware, food containers, appliances – are where it expects them to be, and there are no pesky humans to get in the way.

They like structure

In an assembly line or a warehouse, the environment and sequence of tasks are strictly organized. This allows engineers to preprogram the robot’s movements or use simple methods like QR codes to locate objects or target locations. However, household items are often disorganized and placed randomly.

Home robots must deal with many uncertainties in their workspaces. The robot must first locate and identify the target item among many others. Quite often it also requires clearing or avoiding other obstacles in the workspace to be able to reach the item and perform given tasks. This requires the robot to have an excellent perception system, efficient navigation skills, and powerful and accurate manipulation capability.

For example, users of robot vacuums know they must remove all small furniture and other obstacles such as cables from the floor, because even the best robot vacuum cannot clear them by itself. Even more challenging, the robot has to operate in the presence of moving obstacles when people and pets walk within close range.

Keeping it simple

While they appear straightforward for humans, many household tasks are too complex for robots. Industrial robots are excellent for repetitive operations in which the robot motion can be preprogrammed. But household tasks are often unique to the situation and could be full of surprises that require the robot to constantly make decisions and change its route in order to perform the tasks.

The vision for household humanoid robots like the proposed Tesla Bot is of an artificial servant capable of handling any mundane task. Courtesy Tesla

Think about cooking or cleaning dishes. In the course of a few minutes of cooking, you might grasp a sauté pan, a spatula, a stove knob, a refrigerator door handle, an egg and a bottle of cooking oil. To wash a pan, you typically hold and move it with one hand while scrubbing with the other, and ensure that all cooked-on food residue is removed and then all soap is rinsed off.

There has been significant development in recent years using machine learning to train robots to make intelligent decisions when picking and placing different objects, meaning grasping and moving objects from one spot to another. However, to be able to train robots to master all different types of kitchen tools and household appliances would be another level of difficulty even for the best learning algorithms.

Not to mention that people’s homes often have stairs, narrow passageways and high shelves. Those hard-to-reach spaces limit the use of today’s mobile robots, which tend to use wheels or four legs. Humanoid robots, which would more closely match the environments humans build and organize for themselves, have yet to be reliably used outside of lab settings.

A solution to task complexity is to build special-purpose robots, such as robot vacuum cleaners or kitchen robots. Many different types of such devices are likely to be developed in the near future. However, I believe that general-purpose home robots are still a long way off.

Ayonga Hereid does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

This article appeared in The Conversation.

Machine Learning at the edge is gaining steam. BrainChip is accelerating this with their Akida architecture, which is mimicking the human brain by incorporating the 5 human senses on a machine learning-enabled chip.

Their chips will let roboticists and IoT developers run ML on device for low latency, low power, and low-cost machine learning-enabled products. This opens up a new product category where everyday devices can affordably become smart devices.

Rob Telson

Rob is an AI thought-leader and Vice President of Worldwide Sales at BrainChip, a global tech company that has developed artificial intelligence that learns like a brain, whilst prioritizing efficiency, ultra-low power consumption, and continuous learning. Rob has over 20 years of sales expertise in licensing intellectual property and selling EDA technology and attended Harvard Business School.

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Casinos and robots? It must be CES time! A few years ago, the only robots at CES were toys. And as the robot toy makers at Ologic can attest, having your robot featured as the leading image for CES was still no guarantee that your robot would make it into production (AMP is pictured above). Luckily Ologic have transferred their consumer electronics experience into building robots of every other kind. And CES now showcases robots of every shape and size, from autonomous cars, trucks and construction robotics, to food production, health and rehabilitation robots. The 2022 CES Innovation Awards recognize a range of robotics technologies as Honorees, and feature three in the “Best of Innovation” category as well.

See & Spray

By John Deere

Best of Innovation

Robotics

Honoree

Vehicle Intelligence & Transportation

See & Spray is a technologically advanced, huge robot for the agriculture industry that leverages computer vision and machine learning to detect the difference between plants and weeds, and precisely spray herbicide only on the weeds. This groundbreaking plant-level management technology gives a machine the gift of vision and reduces the use of herbicide by up to 80 percent, benefiting the farmer, the surrounding community and the environment. This revolutionary approach of technology is unprecedented in both the technology and agriculture industries.

Leica BLK ARC

By Leica Geosystems, part of Hexagon

Best of Innovation

Robotics

The BLK ARC is an autonomous laser scanning module for robotics applications. It provides a safe and autonomous way to capture, in 3D, the images and data of areas that are difficult or dangerous for humans to reach. Professionals in architecture/engineering/construction (AEC), manufacturing, plant, public safety, and media and entertainment attach the BLK ARC to a robotic carrier to capture data that is used to build 3D models and recreate situations. For example, man-made or natural disasters, automotive plants, bridges, and movie location sets. The product’s speed, accuracy, flexibility, and modular design provides fully autonomous mobile LiDAR scanning and navigation.

WHILL Model F – Foldable Personal EV

By WHILL, Inc.

Best of Innovation

Accessibility

WHILL Model F is a foldable personal electric vehicle for everyone, including seniors and people who have difficulty walking. Unlike wheelchairs, which are typically built for patients in a medical environment, Model F is designed to fit an active lifestyle for everyday use. It is lightweight and foldable, which makes it easy to load in cars and convenient when traveling by air. The WHILL smartphone app allows you to drive and lock the Model F remotely, as well as check key device information such as total mileage and battery level.

DROWay – Intelligent UATM Ground Control Platform

By CLROBUR Co., Ltd. / HANSEO UNIVERSITY

Honoree

Drones & Unmanned Systems

DROWay is an integrated and expansional multi-mobile platform that goes beyond former mobility control services. (Part of DROW4D service) – Multi-heterogeneous mobility HW integrated control and real-time monitoring control system – Automatic multiple flight path generation and flight simulation in a 4D airspace(corridor) – Indoor/Outdoor Swarm flight & simulation (DROW World/DROW ART Manager) – AI based ground control data managing & analysis

DJ25 – Fuel cell powered VTOL (with JOUAV)

By Doosan Mobility Innovation

Honoree

Drones & Unmanned Systems

DJ25 is the world’s first hydrogen fuel cell VTOL(Vertical Take Off and Landing) commercial drone solution. Doosan and JOUAV successfully integrated its advanced PEMFC(Proton-Exchange Membrane Fuel Cell) technology to VTOL air frame, With this collaboration make the flight time achieve up to 5 and half hours. DJ25 can cover up to 500km in a single flight, and it is suitable for long distance inspections, large scale site surveying and mapping compared to the ordinary batter drone. and also hydrogen-powered version has low noise and no vibration during power generation. It is stable and efficient when loading various mission equipment.

Mini GUSS

By GUSS Automation

Honoree

Drones & Unmanned Systems

Mini GUSS is the world’s first and only autonomous vineyard, hops, berry, and high density orchard sprayer.

Drone Charging Station “ON STATION”

By ISON

Honoree

Drones & Unmanned Systems

High Mast Drone Charging Station consists of a pole, drone hangar, control box and other accessories if necessary by the users. The high mast pole can raise and lower automatically by the control box and the drone hangar can be stored up to 50 feet tall so drone hangar or other accessories such as anemometer, CCTV camera, rain sensor, solar panel module, LED lights or even the weapon (M60) can be added on the pole for the purpose of end user’ s circumstance.

Delivery AMR：Mighty-D3

By Piezo Sonic Corporation

Honoree

Drones & Unmanned Systems

The AMR for transportation: Mighty-D3 is designed based on the technology of Japanese lunar exploration robots, and uses Piezo Sonic Motor for the steering mechanism. It is designed based on Piezo Sonic’s 3C concept (Cool, Cute, Compact), so it has both design and functionality. Mighty-D3 is capable of climbing over bumps of up to 15cm, turning on the spot, and moving horizontally, allowing it to avoid obstacles and travel autonomously to its destination in both outdoor and indoor environments. Mighty-D3 can be used as a transportation support robot for urban areas, hospitals, commercial facilities, and big apartments.

WasteShark

By RanMarine Technology BV

Honoree

Drones & Unmanned Systems

To contribute to the huge challenge of cleaning and monitoring our world’s waters, RanMarine Technology developed the patented WasteShark. It is the world’s first autonomous aquadrone designed for clearing marine plastic waste. At a running cost of 20% of other marine waste removal solutions and with zero emission operation, the intelligent WasteShark is easy to operate and maintain. The WasteShark is our first model and our roadmap includes products based on the WasteShark such as the OilShark and MegaShark. It is accessible to public and private entities that aim to contribute to restoring the marine environment to its natural state.

SPIDER-GO ; Warehouse Inventory Automation System

By TACTRACER CO., LTD.

Honoree

Drones & Unmanned Systems

SPIDER-GO is an automated warehouse inventory system that periodically scans and updates the inventory status in real time. The key features include automated modelling of the warehouse layout, presenting the inventories on the 3D map, and inspecting the inventory status through remote control. It is also equipped with functions that allow monitoring by CCTV, detecting fire, and remote updating. Conventional warehouse management systems have had issues like frequent errors in loading and picking, discrepancies between the system and the actual inventories due to human input errors. SPIDER-GO can innovatively improve the visibility and efficiency for proper warehouse inventory management.

Whiz Gambit – 2-in-1 AI-powered cleaning & disinfection solution

By Avalon SteriTech Limited

Honoree

Robotics

Whiz Gambit, is a 2-in-1 AI-powered cleaning and disinfection robotic solution jointly developed by Avalon SteriTech and SoftBank Robotics Group. The robot is the first disinfection robot to achieve Performance Mark by SGS, the world’s leading verification and testing company, with proven efficacy to eliminate >99% microbial bioburden. Importantly, Whiz Gambit greatly minimizes potential health risks in communal areas with its effective, consistent cleaning and disinfection performance. It has been a trusted partner for hospitality groups, shopping malls, schools, and offices around the world.

The Essentials; The Ultimate Building Blocks for Mobile Robots

By Avular

Honoree

Robotics

Avular proudly presents the world’s first end-to-end solution for mobile robots. The Essentials are modular hardware and software building blocks, specifically designed to (1) rapidly build new mobile robot applications, (2) turn existing machines into autonomous ones, and (3) develop robust and scalable end-products. The Essentials cover all the core functionalities a mobile robot needs, allowing you to focus on your specific application. Our products already enable entrepreneurs and engineers to build robots that make the world a better place in the fields of food, safety, energy, and more.

CygLiDAR_h3 (2D/3D Dual Solid State LiDAR)

By CYGBOT CO,. LTD.

Honoree

Robotics

It is a Solid State LiDAR product that does not operate mechanically, and it can measure 2D and 3D at the same time. Most robots use 2D LiDAR to identify their position and 3D Camera to determine obstacles while driving. CygLiDAR, you can get 2D and 3D data together with one product. CygLiDAR allows robots to reduce the number of sensors used and to produce robots that are competitive in design and cost.

Doosan NINA (New Inspiration New Angle)

By Doosan Robotics

Honoree

Robotics

As an achievement of Project NINA (New Inspiration. New Angle.), Doosan created an unprecedented camera robot system that empowers everyone to become professionals, opening next-level creativeness. To democratize filming robots, Doosan innovated software with intuitive UI that helps content creators to film effortlessly, including sharing presets of camera movement on Doosan’s platform. Another key part of the system is that the robot shoots 360-degrees and tracks shooting objects, simplifying complex camera moves to allow filming at any angle. It can be controlled by hand and/or joypad so that people with no experience with robot operations can handle it without difficulties.

DOTSTAND V1

By DOTHEAL Co.,Ltd.

Honoree

Computer Peripherals & Accessories, Fitness & Sports, Robotics

Using computers for an extended number of hours with poor posture results in forward head posture syndrome (FHP), a very common problem that causes neck pain and fatigue. Doctor visits and therapy are both time consuming and expensive. DOT STAND is a patent-pending, smart monitor stand that uses an AI sensor to analyze the user and automatically self-adjusts any monitor’s position to induce better posture – without the user even knowing it. DOT STAND relieves pain and improves concentration and work efficiency and improves average cervical curve ARA by up to 8%.

Hey-Bot(AI-based, Smart Disinfection&Guide Robot)

By Hills Engineering co.,ltd. / HANSEO UNIVERSITY

Honoree

Robotics

‘Hey-Bot’ is an AI-based self-driving disinfection and guide robot for convention centers, hospitals, negative pressure wards and other important but vulnerable places. The robot protects people from the coronavirus pandemic by minimizing chance of getting infection. It effectively kills the virus and limits unnecessary social contacts in guiding one’s way to his or her destination and sanitizing a given area based on its self-driving, guide and disinfection functions. ‘Hey-Bot’ is highly advanced intelligent Disinfection & Guide robot that can open safe and convenient “with coronavirus” era where people can be reassured for living and working.

RGB-D AI Robot

By Industrial Technology Research Institute (ITRI)

Honoree

Robotics

The RGB-D AI Robot is the world’s first collaborative robot that includes smart 3D vision as a built-in standard for high-precision object recognition. The integration of a 3D camera and MEMS laser scanning projector, along with the auto labeling technology, allows the robot to quickly learn through visually acquired data and perform hand-eye coordination skills. The miniature size of the optical sensor makes it easy to install in robotic arms and can lower installation costs. This innovation can be applied to human-robot collaboration in both manufacturing and service sectors.

Lumotive Meta-Lidar Platform

By Lumotive

Honoree

Robotics, Vehicle Intelligence & Transportation

The Lumotive Meta-Lidar Platform is the mobility industry’s smallest and most cost-effective 3D sensing solution comprising a Lumotive tiny lidar sensor with patented beam steering technology, real-time control software, and a reference system design. Unlike previous generation lidar systems that use mechanical spinning assemblies and are known for being big and expensive, Lumotive’s solution is tiny and scalable for a range of size, performance and power requirements.  The Meta-Lidar Platform removes barriers to greater proliferation of 3D sensing in automotive, industrial and consumer applications.

Monarch Tractor, MK-5

By Monarch Tractor

Honoree

Robotics

Monarch Tractor, the world’s first fully electric, driver optional, smart tractor, enhances farmer’s existing operations, alleviating labor shortages, and maximizing yields. The award-winning Monarch Tractor combines electrification, automation, machine learning, and data analysis to set a new standard in tractor technology and capabilities.

Ted

By Naio technologies

Honoree

Robotics

Ted offers a sustainable, serviceable and smart winegrowing solution combining high edge technology in robotics and AI. Ted is the first robot dedicated to vineyards, an alternative to the use of herbicides that respects your soils and improves your working conditions.

Autonomous Box Truck

By Gatik

Honoree

Vehicle Intelligence & Transportation

Gatik, the leader in autonomous Middle Mile logistics, delivers goods safely and efficiently using its fleet of light and medium duty trucks. The company focuses on short-haul, B2B logistics for Fortune 500 retailers such as Walmart and Loblaw. Gatik’s Class 3-6 autonomous box trucks are live for customers in multiple markets including Texas, Arkansas, Louisiana and Ontario. In April 2021, Gatik launched its strategic collaboration with Isuzu North America, marking the first time a global OEM is working in the medium duty category with a Middle Mile trucking company. Gatik’s autonomous driving.

XenoLidar-X

By XenomatiX – True-Solid-State-LiDAR

Honoree

Vehicle Intelligence & Transportation

XenoLidar-X is a true-solid-state LiDAR designed for high resolution and accurate analysis of the vehicle’s surroundings. It is a stand-alone, off-the-shelf solution with no moving parts, intended for autonomous and industrial applications. XenoLidar-X comes in two versions: Xact for mid-range, and Xpert for long-range measurements. Both versions include XenoWare, the 3D point cloud software enabling perception solutions in ADAS and up to fully autonomous driving.

4Sight M

By AEye, Inc.

Honoree

Vehicle Intelligence & Transportation

4Sight M is a high-performance, software-configurable adaptive LiDAR sensor designed to meet the diverse performance and functional requirements of autonomous and partially automated applications. Its solid-state reliability, combined with industry-leading LiDAR performance (extended range from 1cm to 1,000 meters), integrated intelligence, advanced vision capabilities (10-20x more accurate than camera-only systems), and unmatched reliability make it an ideal fit for mobility, trucking, transit, construction, rail, intelligent traffic systems, and aerospace and defense markets.

Eos Embedded Perception Software

By Algolux

Honoree

Vehicle Intelligence & Transportation

Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicle (AV) systems today are not able to support many driving environments, weather conditions, and challenging scenarios. Driving in low light, snow, rain, and even tunnels are just some of the situations where perception systems often fail due to a lack of robustness. Eos is an award-winning embedded perception solution that delivers up to 3x improved accuracy across all conditions, especially in low light and harsh weather. Its efficient end-to-end deep learning architecture can be quickly personalized to any camera lens/sensor configuration or for multi-sensor fusion.

Nova Lidar

By Cepton Technologies

Honoree

Vehicle Intelligence & Transportation

Nova is a miniature, wide-angle, near-range lidar built for modern vehicles at a target volume price below $100, to help increase vehicle safety and enable autonomous driving capabilities. Powered by Cepton’s patented MMT®, Nova can be elegantly embedded all around a vehicle to provide a complete 360° view of its immediate surroundings without disrupting its design aesthetics. Nova is designed to help minimize perception blind spots and reduce accidents and vehicle damage. Nova is a transformational sensor that fundamentally changes the game for near-range sensing applications.

Automated Steering Actuator

By Nexteer Automotive

Honoree

Vehicle Intelligence & Transportation

Nexteer’s Automated Steering Actuator: High Availability, Output & Durability offers high safety coverage through a combination of software, electrical hardware, mechanical & sealing redundancies – plus increased durability & reliability performance required for higher loads due to increasing vehicle weights (battery mass) & more demanding use-cases of Shared Autonomous Vehicles without driver manual back-up. Our Automated Steering Actuator facilitates broader adoption of Shared Autonomous Vehicles (SAVs), like people movers, to be capable of higher loads and higher speeds, compared to current last-mile, geofenced and neighborhood vehicles on the market.

1-box Brake System for Highly Autonomous Driving

By Mando Corporation

Honoree

Vehicle Intelligence & Transportation

Mando’s Integrated Dynamic Brake is a 1-box electro-hydraulic brake system replacing and integrating multiple components of a traditional brake system into one unit. This promotes the reduction in vehicle mass and simplifying the assembly step by requiring less electrical and hydraulic components. ‘IDB for Highly Autonomous Driving’ is a world-first product that secures braking functional redundancy contained within the same 1-box system, eliminating the need for additional components. Moreover, in the unlikely event of failure, it provides fully redundant brake functionality and performance.

Hammerhead

By NODAR

Honoree

Vehicle Intelligence & Transportation

NODAR’s Hammerhead camera-based 3D vision software technology is a crucial component in the development of ADAS and autonomous vehicles bringing safety, advanced performance, and cost-effectiveness to the automotive market. NODAR’s 3D vision platform, Hammerhead, delivers reliable, ultra-precise, and real-time 3D sensing at long-range (up to 1000 meters), providing better than LiDAR-quality at the price point of camera technology. Between 2025 and 2030 a projected 250 million vehicles will require L2 and above autonomy to understand their environment and provide the high-level of safety required as autonomous systems control more of the driving function.

TriEye SEDAR

By TriEye

Honoree

Vehicle Intelligence & Transportation

TriEye’s SEDAR (Spectrum Enhanced Detection And Ranging) is the ultimate imaging and ranging solution for automated driving applications. SEDAR’s sensing modality, uniquely operating in the Short-Wave Infrared (SWIR) spectrum, enables imaging and 3D mapping of the road within all visibility conditions – in one sensory modality The SEDAR is based on two significant world’s first innovations: TriEye’s Raven (HD CMOS-based SWIR sensor) and TriEye’s UltraBlaze (Eye-safe SWIR pulsed laser illumination source). TriEye’s first-of-its-kind technology is suited for mass production, offering a 10X cost reduction compared to current LiDAR solutions on the market.

Phoenix Perception Radar

By Arbe

Honoree

Vehicle Intelligence & Transportation

Arbe’s Perception Radar, Phoenix, revolutionizes autonomous vehicle sensing, providing unmatched safety to the market. Ultra-high resolution transforms radar as a sensor to support advanced perception capabilities at mass market price, with top performance in all environments, weather, and lighting conditions. It is the first radar to detect stationary objects — a notorious stumbling block for autonomous radars — meeting NHTSA and NCAP requirements and resolving the factors behind ADAS and Autopilot related accidents. With an Advanced Free Space mapping and object tracking in all corner cases, Phoenix closes the sensor gap to achieve truly safe autonomous driving and Vision Zero.

‘Real-to-real’ – Unique ADAS Technology

By Cognata LTD – Ella Shlosberg

Honoree

Vehicle Intelligence & Transportation

Cognata is proud to launch its ‘real-to-real’ technology, which accelerates the global program for ADAS validation in order to meet worldwide regulatory requirements. The proprietary AI technology developed with Cognata transforms the super-high resolution data set to sensor inputs “as seen” by new sensors in new vehicle applications. Meaning, it is now possible to re-use previously collected video data to test a camera in a new position or with a new optical path and record multiscopic images and apply AI SLAM – based image transformation.

Robot Express for Smart Transportation and Logistics

By Mindtronic AI

Honoree

Smart Cities

The Robot Express is a smart logistic service that leverages the public transportation network for delivering goods. The advantage is that the sender and receiver can utilize the bus stop as express station. With the density and frequency of the shuttle bus, both service coverage and delivery time can be improved. Another advantage is energy saving because the shuttle not only transport the passengers but also the goods at the same time.

Maicat

By Macroact Inc.

Honoree

Smart Home

The social robot Maicat incorporates AI into Robotics, combining beneficial characteristics of a cute, engaging companion pet with the intelligence of AI, generating empathetic and personalized experiences for the user. Autonomous control and AI technology enable the robot to understand and adapt to its environment while its mobility, passive and active sensors support it to navigate and operate in the home, and allow an easy integration with other smart home technology via third-party Application, making it the center of the smart home. Being with Maicat adds another dimension to your life!

Mind-linked Bathbot

By Amorepacific

Honoree

Health & Wellness

Mind-linked Bathbot is the first beauty solution that produces bath bombs with customized fragrances and colors instantly, based on an individual’s electroencephalogram (EEG) data. The EEG signals are measured in real-time using a wearable headset and combined with a technology that has been developed to enable the quantitative evaluation of emotional indicators. These emotional indicators enable the identification of the fragrance and color that will provide a unique experience to the user. This user-optimized information is then transmitted to the Bathbot (bath bomb-making robot). This is the first technological invention to produce a customized bath bomb within a minute.

AVATAR 3D system (AVT-2020-700)

By AVATAR

Honoree

Health & Wellness

A next-generation system for quantification of animal behavior experiments that can replace the existing preclinical scoring that consists of human standards. As a fusion system of multi-vision hardware and AI software, all behaviors of mice, a representative animal of preclinical testing, can be quantified in real time with markerless and simulated in a 3D virtual space.

rebless

By H ROBOTICS INC.

Honoree

Health & Wellness

rebless is an FDA-registered robotic, exercise therapy device for both upper and lower limbs, providing motion to the elbow, wrist, ankle, and knee joints. With multiple operating modes, rebless allows for passive, active, active-assisted and active-resisted exercise and range of motion measurement, so therapy can be customized based on each individual patient’s condition and progress. Continuous Passive Motion (CPM) and Assist-as-Needed technology allow patients to change exercising modes depending on their rehabilitation abilities.

OMO Smart Trash Can

By GD International Inc.

Honoree

Home Appliances

The OmO Smart Can is a new and first of it’s kind self-sealing and touchless trash can.  A built-in motion sensor and compatible feature with voice assistants like Alexa and Google Assistant gives you a hand-free approach to tidying up.  When it’s time to take out the trash, an internal thermal sealing mechanism seals trash in and opens the inner bin for a ready to throw bag.  A replacement bag automatically deploys once the bin closes back up and is ready for the next dispense.

Narwal World First Self-Cleaning Robot Mop and Vacuum

By Narwal Robotics Corporation

Honoree

Home Appliances

Narwal J2 is a robotic cleaner with automatic mop-cleaning base station. Users can select between vacuum or mop modules to meet their cleaning needs. The spinning mop with 10N pressure applied against the floor, which greatly enhances the cleaning effect. It utilizes Lidar and SLAM technologies to intelligently navigate and map the environment. When the intelligent algorithm detects dirtiness of mopping pads, it automatically returns to base station to wash pads and resume work from where it stopped. Users do not need to deal with dirty mops at any time, saving hands from coming in contact with allergens or dirt.

Nailbot

By Preemadonna Inc.

Honoree

Home Appliances

Nailbot is a connected, at-home manicure device that instantly prints on nails any photo, emoji, image or any self-created design. Along with the product experience, comes a built-in community of Gen Z creators via a mobile app art marketplace. Preemadonna is the maker of Nailbot.

The full list of CES Innovation Award Honorees is here,

Matt Bilsky, founder and CEO of FLX Solutions, discusses the snake-like robot he invented called the FLX BOT. The FLX BOT consists of modular links, each with a joint that can extend and rotate to get into tight spaces. Each link includes sensors including inertial measurement units and a camera. The robot is used to navigate and work in challenging environments, such as above ceilings and within walls. Matt discusses the key innovations of his product as well as his academic and entrepreneurial journey that led him to the FLX BOT.

Matt Bilksy

Matt Bilsky, PhD, PE is the inventor of the FLX BOT, a licensed Professional Engineer, a Mechanical Engineering professor at Lehigh University, and a former repair/maintenance contractor. In 2017, he was awarded with the Lehigh University Entrepreneurship Educator of the Year. Matt has a Mechanical Engineering Ph.D. from Lehigh University focused on smart product design, Technical Entrepreneurship, and mechatronics. He holds two additional Lehigh degrees: a BS in Mechanical Engineering with an Electrical Engineering minor and a Master of Engineering degree also in Mechanical Engineering. Since he was a child Matt has been an innovator. In his basement shop he designed and built numerous electronic gadgets. In 2003 he started his first company, Mattcomp Services LLC, offering computer repair, networking, home theater, and handyman services. He also created a web hosting company in 2005, Mattcomp Hosting, including all necessary back-end components on dedicated servers.

Links

• Download mp3 (25.1MB)
• FLX Solutions
• FLX Youtube channel
• Matt’s Portfolio
• Matt’s Youtube channel

In this episode, Lauren Klein interviews Muralidharan Arikara, CEO of Xarpie Labs. Xarpie Labs creates visualization and simulation experiences within the retail, healthcare, and defense industries. Arikara describes how Xarpie Labs grew as part of the Machani Group, which has decades of experience in automotive manufacturing, into an innovator in virtual and augmented reality. He elaborates on the role of Xarpie Lab’s virtual reality and augmented reality experiences in allowing real estate customers a vision of properties from a distance. Arikara also paints a picture of Xarpie Labs’ augmented reality tools, including a project for a museum to visualize old gramophones for visitors and an air conditioning troubleshooting tool for technicians.

Muralidharan Arikara

Muralidharan Arikara is an entrepreneur and the CEO of Xarpie Labs. Arikara is an engineer by training, and worked in the clean energy industry prior to his current role. In addition to his role as CEO at Xarpie Labs, he is also a member of the advisory board of several startups in the energy and consumer segments.

Links

• Download mp3 (16.8 MB)
• Xarpie Labs Virtual Employee Onboarding Program
• LinkedIn
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• Subscribe to Robots using RSS
• Support us on Patreon

In this episode, Shihan Lu interviews Dr. Heather Culbertson, Assistant Professor in the Computer Science Department at the University of Southern California, about her work in haptics. Dr. Culbertson discusses the data-driven realistic texture modeling and rendering, haptic technologies in the social touch, the combination of haptics and robots, expectations and obstacles of haptics in the next 5 years.

Heather Culbertson

Heather Culbertson is a Gabilan Assistant Professor of Computer Science at the University of Southern California. Her research focuses on the design and control of haptic devices and rendering systems, human-robot interaction, and virtual reality. Particularly she is interested in creating haptic interactions that are natural and realistically mimic the touch sensations experienced during interactions with the physical world. Previously, she was a research scientist in the Department of Mechanical Engineering at Stanford University where she worked in the Collaborative Haptics and Robotics in Medicine (CHARM) Lab. She received her PhD in the Department of Mechanical Engineering and Applied Mechanics (MEAM) at the University of Pennsylvania in 2015 working in the Haptics Group, part of the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory.

Links

• Download mp3 (14.8 MB)
• Culbertson’s research website
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• Support us on Patreon

In this episode, Audrow Nash interviews Bernt Børnich, CEO, CTO, and Co-founder of Halodi Robotics, about Eve (EVEr3), a general purpose full-size humanoid robot, capable of a wide variety of tasks.  Børnich discusses how Eve can be used in research, how Eve’s motors have been designed to be safe around humans (including why they use a low gear ratio), how they do direct force control and the benefits of this approach, and how they use machine learning to reduce cogging in their motors.  Børnich also discusses the longterm goal of Halodi Robotics and how they plan to support researchers using Eve.

Below are two videos of Eve. The first is a video of how Eve can be used as a platform to address several research questions.  The second shows Eve moving a box and dancing.

Bernt Børnich

Photographer: Tonje Kornelie

Bernt Børnich is the CEO and CTO of Halodi Robotics, and the inventor of their Revo1 motors. He holds a bachelor of robotics and nano-electronics from the University of Oslo.

Links

• Download mp3 (16.4 MB)
• Halodi’s homepage
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Support us on Patreon

In this episode, Audrow Nash speaks with Ian Bernstein, Founder and Head of Product at Misty Robotics, about a robotics platform designed for developers called Misty II.  Bernstein discusses the motivation behind making a robotics platform for developers (relating it to personal computers), Misty II’s hardware extensibility and software “skills,” and the future direction of Misty Robotics.

A video introducing the Misty II platform:

Ian Bernstein

Ian Bernstein is Founder and Head of Product at Misty Robotics, a spin-off company from Sphero, Inc. focused on building personal robots for the home and office. In this role, Bernstein leads Misty Robotics’ product development and design. Prior to Misty Robotics, Bernstein served as Founder and Chief Technology Officer at Sphero, Inc. that has shipped more than 3 million robots to date. Bernstein joined TechStars in 2010 with Sphero co-founder Adam Wilson and created Sphero, the original app-enabled robotic ball. Bernstein has had a lifelong passion for robotics and creation and has been building robots since he was 12. Ian holds a BS in Electrical and Electronics Engineering from Colorado State University.

Links

• Download mp3 (13.8 MB)
• Misty Robotics’ homepage
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• Support us on Patreon

In this episode, Audrow Nash interviews Dor Skuler, CEO and co-founder of Intuition Robotics, about a socially assistive robot for older adults named ElliQ. Skuler discusses the motivation for ElliQ, how it infers context and changes its behavior accordingly, and how ElliQ adapts its behavior over time.

Below is a video that shows what interactions with ElliQ look like.

Dor Skuler

Dor Skuler has co-founded five ventures, the most recent being Intuition Robotics. Skuler holds an MBA and Master’s of Science in Marketing from Temple University, has co-authored ‘Cloud Computing: Business Trends and Technologies’ published by Wiley in 2016 and holds board level advisory and director roles for several telecoms, cyber security and tech-led social impact ventures.

Links

• Download mp3 (17.1 MB)
• ElliQ’s webpage
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• Support us on Patreon

In this interview, Audrow Nash interviews Gabriel Lopes, Robot and Control Scientist at Robot Care Systems, and Bernt Børnich, CEO and Co-founder of Halodi Robotics.

Gabriel Lopes speaks about an assistive walker with additional functionality.  Lopes discusses how the walker can be used, including driving up to the person, helping them stand up, exercise, and make video calls.  He also discusses building a software language for non-technical people that work with older adults. Lopes also speaks about the future of their company.

Bernt Børnich speaks about the humanoid platform at Halodi Robotics. Børnich’s long-term goal is to create an affordable home robot. He discusses the design and form factor of this robot. This includes the custom motor designed for high torque, and how the robot can “lean in” from a joint at its ankle. Børnich discusses the timeline, speculated cost, and working with investors on the long term goal of building an affordable humanoid robot.

Links

• Download mp3 (13.6 MB)
• Subscribe to Robots using iTunes
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• Support us on Patreon

Image from the South China Morning Post

In this episode, Audrow Nash speaks with Karl Weaver (魏卡爾), formerly the Original Equipment Manufacturer Business Development Director for Oasis Smart SIM. Weaver discusses how wearable technology is growing as a form of payment system in China. He speaks about wireless technology, including Near-Field Communications (NFC) and Embedded SIM cards (eSIM), in wearable technology and in other applications, such as bike rental.

Karl Weaver (魏卡爾)

Since the recording of this interview, Karl has begun working for ARM promoting eSIM and iUICC to Greater China and Asia.

Karl Weaver (魏卡爾) previously worked as the Original Equipment Manufacturer Business Development Director (North America and Northeast Asia) for Oasis Smart SIM. Prior to Oasis, Karl worked for Rivetz Corp, a Massachusetts-based start-up to promote developer tools for design-in of TEE-enables applications on Smartphones for payment and security. Karl also spent 5 years working in China for Gemalto (and Trustonic) as liaison and evangelist of embedded Mobile Near-Field Communications Payments & TEE security technologies to the OEM Smartphone/Tablet PC ecosystem. Weaver has a B.S degree in Business Management from Salve Regina University and a Certification in Mandarin Chinese Language, Customs, and Culture from National Taiwan Normal University.

Links

• Download mp3 (17.5 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Support us on Patreon

Mike Toscano, the former president of the Association for Unmanned Vehicle Systems International, emphatically declared at the September RobotLab forum that “anyone who claims to know the future of the [robotics] industry is lying, I mean no one could’ve predicted the computing mobile revolution.” These words acted as a guiding principle when walking around RoboBusiness in Silicon Valley last week.

The many keynotes, pitches and exhibits in the Santa Clara Convention Center had the buzz of an industry racing towards mass adoption, similar to the early days of personal computing. The inflection point in the invention that changed the world, the PC, was 1995. During that year, Sun Microsystems released Java to developers with promise of “write once, publish anywhere,” followed weeks later by Microsoft’s consumer software package, Windows ’95. Greater accessibility led to full ubiquity and applications unthinkable by the original engineers. In many ways, the robot market is standing a few years before its own watershed moment.

In my last post, I highlighted mechanical musicians and painters, this week it is time to see what is cooking, literally, in robotics. Next year, startup Moley plans to introduce the “first fully-automated and integrated intelligent cooking robot,” priced under $100,000. It already has a slick video that is reminiscent of Lily’s Robotics’ rise to the headlines; needless to say Moley has created quite a stir in the culinary community.

Austin Gresham, executive chef at The Kitchen by Wolfgang Puck is very skeptical, “Professional chefs have to improvise constantly as they prepare dishes. If a recipe says to bake a potato for 25 minutes and the potatoes are more or less dense than the previous batch, then cooking times will vary. I would challenge any machine to make as good a mashed potato (from scratch).” Gresham’s challenge is really the crux of the matter, creativity is driven by human’s desire for food, without taste could a robot chef have the intuition to improvise?

Acting as a judge of the RoboBusiness Pitch Fire Competition, I met entrepreneurs undiscouraged by the market challenges ahead. In addition, throughout my Valley visit, I encountered five startups building commercial and consumer culinary applications. Any time this happens within such a short timespan, I stop and take notice. Automated restaurants seem to be a growing trend across the nation with a handful of upstarts on both coasts. Eatsa is a chain of quinoa-salad restaurants sans cashiers and servers. Customers order via mobile devices or on-site kiosks, picking up their ready dishes through an automated floor-to-ceiling lockbox fixture. However, behind the wall Eatsa has hourly workers manually preparing the salad bowls. Cafe X in San Francisco offers a completely automated experience with a robot-arm barista preparing, brewing and serving espressos, cappuccinos, and Americanos. After raising $5 million from venture investors, Cafe X plans to expand with robot kiosks throughout the city. Probably the most end-to-end automated restaurant concept I visited can be found tucked away on Berkeley University’s Global Campus called BBox by Nourish. BBox is currently running a trial on campus and planning to open its first store next year to conquer the multi-billion dollar breakfast market with egg sandwiches and gourmet coffee (see video below).

According to Nourish’s CEO Greg Becker, BBox will “reengineer the food ecosystem, from farm to mouth.” Henry Hu, Cafe X’s founder, also aims to revolutionize “the supply chain, recipes, maintenance, and customer support.” To date, the most successful robotic concept is Zume Pizza. Founder Julia Collins made headlines last year with her groundbreaking spin on the traditional pizzeria. Today she is taking on Dominos dollar for dollar in the San Francisco area, delivering pies in under 22 minutes. Collins, a former Chief Financial Officer of a Mexican restaurant chain, challenges the food industry, “Why don’t we just re-write the rules— forget about everything we learned about running a restaurant?” Already, Zume is serving hundreds of satisfied customers daily, proving at least with pizza it is possible to innovate.

“We realized we could automate more of the unsafe repetitive tasks of operating a kitchen using flexible, dynamic robots,” explains Collins, who currently employees over 50 human workers that do everything from software engineering to supervising the robots to delivering the pizza. “The humans that work at Zume are making dough from scratch, working with farmers to source products, recipe development—more collaborative, creative human tasks. [We have] lower rent costs because we don’t have a storefront; delivery only and lower labor costs. We reinvest those savings into locally sourced, responsibly farmed food.” Collins also boasts that her human workforce has access to free vision, dental, and health insurance due to the cost savings.

Even Shake Shack could have competition very soon as Google Ventures-backed Momentum Machines is launching an epicurean robot bistro in San Francisco’s chic SoMa district later next year. The machine that has been clocked at 400 burgers an hour, guarantees “to slice toppings, grill a patty, assemble, and bag the burger without any help from humans,” at prices that “everyone can afford.” Momentum’s proposition prompted former McDonald’s CEO Ed Rensi to controversially state that “it’s cheaper to buy a $35,000 robotic arm than it is to hire an employee who’s inefficient making $15 an hour bagging french fries.” Comments like Rensi’s do not further the industry, in fact it probably led to the controversy last month with the launch of Bodega, an automated convenience store that even enraged Lin-Manuel Miranda below.

The bad press was multiplied further by Elizabeth Segran’s article in Fast Company, which read, “the major downside to this concept — should it take off — is that it would put a lot of mom-and-pop stores out of business.” Founder Paul McDonald responded on Medium, “Rather than take away jobs, we hope Bodega will help create them. We see a future where anyone can own and operate a Bodega — delivering relevant items and a great retail experience to places no corner store would ever open.” While Bodega is not exactly a robotic concept, it is similar to the automated marketplace of AmazonGo with 10 computer vision sensors tracking the consumer and inventory management via a mobile checkout app. “We’re shrinking the store and putting it in a box,” said McDonald. The founder has publicly declared war on 7-Eleven’s 5,000 stores, in addition to the 4 million vending machines across the US. Realizing the pressures to innovate, last year 7-Eleven made history with the first drone Slurpee delivery. “Drone delivery is the ultimate convenience for our customers and these efforts create enormous opportunities to redefine convenience,” said Jesus H. Delgado-Jenkins, 7-Eleven EVP and Chief Merchandising Officer. “This delivery marks the first time a retailer has worked with a drone delivery company to transport immediate consumables from store to home. In the future, we plan to make the entire assortment in our stores available for delivery to customers in minutes. Our customers have demanding schedules, are on-the-go 24/7 and turn to us to help navigate the challenges of their daily lives. We look forward to working with Flirtey to deliver to our customers exactly what they need, whenever and wherever they need it.”

As mom & pop stores compete for market share, one wonders with more Kitchen OS concepts if home cooked meals will join the list of outdated cultural trends. Serenti Kitchen in San Francisco plans to bring the Keurig pod revolution to food with its proprietary machine that includes prepared culinary recipe pods that are dropped into a bowl and whipped to perfection by a robotic arm (see above). Serenti Founder Tim Chen was featured last year at the Smart Kitchen Summit, which reconvenes later this month in Seattle. Chen said, “We’re building something that’s quite hard, mechanically, so it’s more from a vision where we wanted to initially develop a machine that could cook, and make cooking easier and automate cooking for the home.” Initially Chen plans to target business catering, “In the near term, we need to focus on placing these machines where there’s the highest amount of density, which is right in the offices,” but long-term Serenti plans to join the appliance counter. Chen explained his inspiration, “Our Mom is a great cook, so they’ve watched her execute the meals. Then realized a lot of it is repetitive, and what recipes are, is essentially just a machine language.” Chen’s observations are shared by many in the IoT and culinary space, as this year’s finalists in the Smart Kitchen Summit include more robotic of inventions, such as Crepe Robot that automatically dispense, cook and flavors France’s favorite snack and GammaChef, a robotic appliance that promises like Serenti to whip up anything in a bowl. Clearly, these inventions will eventually lead to a redesign of the physical home kitchen space that is already crowded with appliances. Some innovators are even using robotic arms tucked away in cabinets and specialized drawers, ovens and refrigeration units that communicate seamlessly to serve up dinner.

The automated kitchen illuminated by Moley and others might be coming sooner than anyone expects; then again it could be a rotten egg. In almost every Sci-Fi movie and television show the kitchen is reduced to a replicator that synthesizes food to the wishes of the user. Three years ago, it was rumored that food-powerhouse Nestle was working on a machine that could produce nutritional supplements on demand, code name Iron Man. While Iron Man has yet to be released to the public, it does illustrate the convergence of 3D printing, robotics and kitchen appliances. While the Consumer Electronics Show is still months away, my appetite has just been whetted for more automated culinary treats, stay tuned!

SharkNinja, a well-known marketer of home consumer products, has entered the American robotic vacuum market with a product that is priced to compete against iRobot’s Roomba line of floor cleaners. Their new ION Robot navigates floors and carpets and docks and recharges automatically. It sells at a very favorable price point to iRobot’s.

SharkNinja has partnered with ECOVACS, a Chinese manufacturer of many robotic products including robotic vacuums and floor cleaners, to custom manufacture the new Shark ION Robot – thus SharkNinja isn’t starting from scratch. [ECOVACS is a big seller in China. On Singles Day (11/11/2016), online via the e-commerce giant Alibaba, ECOVACS sold $60.2 million of robotic products, up from $47.6 million in 2015. The star performer was a DEEBOT robotic vacuum which sold 135,000 units. The ECOVACS window-cleaning robot was another standout product, with more than 10,000 units sold.]

iRobot’s stock took an 18% negative hit – perhaps on the news of the product launch by SharkNinja, or perhaps because some prominent analysts downgraded their ratings of the company saying that iRobot is susceptible to a lower-cost similarly capable well-regarded branded product. The SharkNinja robotic vacuums fits those criteria.

SharkNinja is a fast-growing vendor of blenders, vacuums and other household products. They displaced Dyson in vacuums by engineering a superior product at a value price point (the Dyson robot vacuum sold for $1,000). SharkNinja, by using disruptive pricing and infomercial marketing, has garnered around 20% of the U.S. market for vacuums in just 10 years. SharkNinja’s non-robotic vacuums and blenders command significant shelf space and are very popular with customers and sellers alike. Thus they are a formidable competitor.

Also this month, SharkNinja raised an undisclosed sum from CDH Investments, a private equity fund with $20 billion of assets under management. CDH said they purchased “a significant equity interest” in SharkNinja.

iRobot’s Defensive Moves

iRobot has been making defensive moves recently. It acquired its two main distributors: Robopolis in Europe and Sales on Demand in Japan. It has used up much of its cash reserve to buy back shares of the company. And it sued what it considered to be patent violations by Hoover, Black & Decker, Bobsweep, Bissell Homecare, and Micro-Star International (MSI) (which manufacturers the Hoover and Black & Decker vacuums).

According to Zacks Equity Research, iRobot just favorably settled with MSI in an agreement where MSI will exit the global robotic cleaning industry and also provide a undisclosed compensation fee to iRobot.

“This settlement represents the first successful milestone on the enforcement effort iRobot initiated earlier this year,” said Glen Weinstein, executive vice president and chief legal officer at iRobot. “The agreement by MSI to exit the robotic cleaning industry signifies the value of iRobot’s intellectual property and the company’s efforts to protect it.”

Nevertheless, iRobot may be vulnerable to an international consumer products company with a full range of consumer products who competes with similar products at lower prices.

]]> https://robohub.org/cujo-smart-firewall-for-cybersecurity/ Mon, 04 Sep 2017 01:35:42 +0000 http://robohub.org/cujo-smart-firewall-for-cybersecurity/

In this episode, MeiXing Dong talks with Leon Kuperman, CTO of CUJO, about cybersecurity threats and how to guard against them. They discuss how CUJO, a smart hardware firewall, helps protect the home against online threats.

Leon Kuperman

Leon Kuperman is the CTO of CUJO IoT Security. Leon has a specialization in Artificial Intelligence, and is applying this expert knowledge of machine learning to his work at CUJO smart firewall. He is also an authority on Web Application Security and Payment Card Industry Data Security Standard (PCI DSS), e-commerce, cloud computing and web application architecture. Before CUJO, he co-founded ZENEDGE, a Web Application Security Platform for Enterprise. He also assisted with the launch of Modnique.com and held the position of CTO at Bidz.com. Prior to Zenedge, Leon founded and led Truition Inc., and early on demand ecommerce platform, winning major clients including Dell Financial Services, MLB, Comet, Philips, NHL, United Airlines and Disney. In his early career, he was the founding co-developer of IBM Net.Commerce currently named IBM Websphere Commerce Suite.

 

 

 

 

 

 

Links

• Download mp3 (14.4 MB)
• CUJO Website
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS

]]> https://robohub.org/smart-trials-self-driving-wheelchair-at-hospital/ Wed, 26 Jul 2017 19:00:53 +0000 http://robohub.org/smart-trials-self-driving-wheelchair-at-hospital/

Image: MIT CSAIL

Singapore and MIT have been at the forefront of autonomous vehicle development. First, there were self-driving golf buggies. Then, an autonomous electric car. Now, leveraging similar technology, MIT and Singaporean researchers have developed and deployed a self-driving wheelchair at a hospital.

Spearheaded by Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and director of MIT’s Computer Science and Artificial Intelligence Laboratory, this autonomous wheelchair is an extension of the self-driving scooter that launched at MIT last year — and it is a testament to the success of the Singapore-MIT Alliance for Research and Technology, or SMART, a collaboration between researchers at MIT and in Singapore.

Rus, who is also the principal investigator of the SMART Future Urban Mobility research group, says this newest innovation can help nurses focus more on patient care as they can get relief from logistics work which includes searching for wheelchairs and wheeling patients in the complex hospital network.

“When we visited several retirement communities, we realized that the quality of life is dependent on mobility. We want to make it really easy for people to move around,” Rus says.

Update: The response to Tertill’s crowdfunding campaign has amazed and delighted us! Pledges totalling over $250,000 have come from 1000+ backers. We’re shipping to all countries, with over a fifth of Tertill’s supporters coming from outside the United States. But the end is near; Tuesday (11 July) is the last full day of the campaign. After that Tertill’s discounted campaign price will no longer be available and delivery in time for next year’s (northern hemisphere) growing season cannot be assured.

Franklin Robotics has launched a Kickstarter campaign for Tertill, their solar-powered, garden-weeding robot.

Tertill lives in your garden, collecting sunlight to power its weed patrol, and cutting down short plants with a string trimmer/weed whacker with almost no intervention required. Available for about $300USD, the fully autonomous Tertill is the first weeding robot available to home gardeners.

Tertill is round, short, has four wheel drive and extreme camber wheels. It uses proprietary algorithms to ensure that it finds as many weeds as it can, using its sensors to distinguish between weeds and crops based on height. As Tertill sees it: small plants are weeds, big plants are crops. But what if you have seedlings? Simply place a plant collar around seedlings to inform Tertill that this plant is wanted.

Tertill doesn’t use a camera for weed discrimination because Franklin wants to put Tertill to work in your garden now. In the not-too-distant future, inexpensive vision systems may reliably distinguish between plants and crops even when both are seedlings. But, according to Franklin, such system are not yet ready.

Tertill is designed such that one robot can easily keep up with the weeds in a typical sized garden (that’s about 100 square feet in the USA). Tertill will usually handle gardens considerably larger than this, but how much larger depends on weather and local weed types. And Terrill’s can work in teams, coexisting harmoniously in the same space. Multiple Tertill robots will simply avoid each other.

Check out the video below:

But Tertill needs a small barrier to keep it from wandering off beyond the borders of your garden. A garden fence, the wooden border of a raised bed, or any sort of edging that is two or more inches tall will work.

Otherwise, Tertill is designed to live in your garden and require very little attention. Summer showers won’t bother it. And, under normal conditions, you won’t have to worry about charging Tertill—the sun will see to that. But, if Tertill has been in the dark for so long (months) that its battery is completely exhausted, a USB connection can be used to charge the battery.

Franklin believes that small, simple robots can help solve big, complex problems. Franklin’s robots aim to help gardeners by reducing the tedium and physical challenge of weeding, making gardening more fun. The data their robots collect helps gardeners garden better, improving yield and quality. Their robots aim to benefit the environment by eliminating the need for herbicides and returning organic matter to the soil.

Click here to visit Franklin’s website and learn more.

China’s second-biggest e-commerce company, JD.com (Alibaba is first), is testing mobile robots to make deliveries to its customers, and imagining a future with fully unmanned logistics systems.

 Story idea and images courtesy of RoboticsToday.com.au.

On the last day of a two-week-long shopping bonanza that recorded sales of around $13 billion, some deliveries were made using mobile robots designed by JD. It’s the first time that the company has used delivery robots in the field. The bots delivered packages to multiple Beijing university campuses such as Tsinghua University and Renmin University. 

JD has been testing delivery robots since November last year. At that time, the cost of a single robot was almost $88,000.

They have been working on lowering the cost and increasing the capabilities since then. The white, four-wheeled UGVs can carry five packages at once and travel 13 miles on a charge. They can climb up a 25° incline and find the shortest route from warehouse to destination.

Once it reaches its destination, the robot sends a text message to notify the recipient of the delivery. Users can accept the delivery through face-recognition technology or by using a code.

The UGVs now cost $7,300 per robotic unit which JD figures can reduce delivery costs from less than $1 for a human delivery to about 20 cents for a robot delivery.

JD is also testing the world’s largest drone-delivery network, including flying drones carrying products weighing as much as 2,000 pounds.

“Our logistics systems can be unmanned and 100% automated in 5 to 8 years,” said Liu Qiangdong, JD’s chairman.

Today we are looking at how to program your NAO Robot for Human Interaction. Watch the video and follow the steps below to get interactive with your robot pal!

1.  Create an animation of movements
   • Right click, select “Create a new box”
   • Select “Timeline”

We want the robot to do 3 things, a five high, a hello, and a goodbye move:

• On the Timeline Edit Box
  • Name: High Five
  • Image: Click “Edit”
    • On the Edit box image
    • Click “Browse” and select a file
  • Click “OK”

Now, as you can remember, if we take it to the box, we can get access to the NAO’s Timeline. Mine now is connected to the PC. So what I’m going to do is I’m going to set some points of the NAO to do some movements. As I have said before on one of my tutorial I’m going to make it set all the joints to the whole body.

We want to make him look like he is doing a high five:

• Right click the arm
  • Click “Stiffen chain on/off”
  • Raise his arm up
• Set joints and keyframe
  • Select “Arms”
• Click “Play” on the Motion Controller

That’s a quite quick high five actually. What we want to do is to actually give him a pause when he got his arm in the air. So, the way we do that is to copy and paste the keyframe.

Grab a few already built in animation, just to show you how much it works:

• Go to Motions>Animations
  • Drag a “Hello” box to the workspace
  • Drag a “Wipe Forehead” box for a goodbye move to the workspace

We want to hear him speak, so:

• Go to Voice
  • Drag a “Speech Recognition” box to the workspace
• Drag a “Switch Case”
  • Connect the “Speech Recognition” box to the “Switch Case” box
  • On the first case, write “Hello” and connect to the “Hello” box
  • On the second case, write “High Five” and connect it to the “High Five” box
  • On the third case, write “Goodbye” and connect it to the “Wipe Forehand” box
• Set parameters of Speech Recognition
  • Word list: Hi; High Five; Goodbye;
  • Play with the threshold to see what works better
  • Click “OK”

So there we have a speech recognition, he will listen to what I am saying and then we will act a motion. Now, what we need to do is to make sure that the robot doesn’t repeat it, so you know, it doesn’t loop back. Before we do that, we are going to:

• Drag 3 “Say” box to the workspace so he can  speak back to us
  • On the “Switch case”, connect the “Hello” case on the “Say” box
    • Localized Text
      • Change the language to English(United States)
      • Write “Hi” on the textbox
  • Connect the “High Five” case on the “Say (1)” box
    • Localized Text
      • Change the language to English(United States)
      • Write “High Five” on the textbox
  • Connect the “Goodbye” case on the “Say(2)” box
    • Localized Text
      • Change the language to English(United States)
      • Write “Goodbye” on the textbox

So, here’s what we are saying, he recognizes it, says a word and does an animation, now what we want to do is we don’t want him to loop, as in he keeps hearing the same sound and maybe he starts to hear himself and repeat himself, so to stop that we need to connect the end of the motion boxes back to the “Speech Recognition” box. A simple output to the input speech.

I am going to make a little change actually, instead of “Hello”, we should put “Hi” here and I’m going to put “Hi” in there which is already done because they have to match otherwise if it doesn’t match he won’t recognize it. So if he hit “Load”

Philip: High Five!

Nao: High Five!

Philip: Goodbye!

Nao: Goodbye!

Philip: Hi!

Nao: Hello!

Brilliant! So that looks likes he’s working very well, so again if we says “Hi”, “High Five” or “Good bye” then he will greet you. If you walk in to room and you say “Hi” to a robot, obviously, he will do his animation and say a speech. Here you can use your imagination and try different things, different animations.

If you liked this article, you may also enjoy these from Robo-Phil:

• Python programming your NAO robot
• Hard at work: A review of the Laevo Exoskeleton

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

The Hyundai Medical Exoskeleton (H-MEX), composed of a high-tech back/leg brace combination device and forearm crutches, is meant to help paraplegics walk again (Photo: Hyundai)

This article was first published on the IEC e-tech website.

Advances in sensors have increased the ability of assistive robots to perform domestic handling and mobility assistance tasks as well as to analyze the environment and individuals around them so that they can carry out monitoring functions. About 4 700 elderly assistance robots were sold globally in 2015, according to the International Federation of Robotics in Frankfurt, which forecasts that sales will increase to 37 500 units between 2016 and 2019.

Robots assisting with healthcare delivery in the home not only increase their users’ autonomy but also have the potential to relieve the burgeoning demands that elderly populations place on health and care services and informal caregivers.

Meanwhile, increasingly sophisticated “companion robots” are being developed to interact with users, make social connections with them and even provide companionship and emotional support, subject to personal choice.

Several IEC Technical Committees (TCs) and Subcommittees (SCs) cooperate on the development of International Standards for the broad range of electrotechnical systems, equipment and applications used in care robots, with an emphasis on safety and interoperability.

Care robots and other assistive robotic devices form part of the wider category of Active Assisted Living (AAL) technologies. All are designed to enhance the quality of life of users and enable them to lead independent lives through the use of Information and Communication Technology (ICT).

The IEC Systems Committee on AAL (SyC AAL), which started work in 2015, has the role of promoting safety, security, privacy and cross-vendor interoperability in the use of AAL systems and services, and of fostering standardization that enables their usability and accessibility.

Human-robot interaction

Assistive robots with sensory and monitoring functions have been in use in healthcare for over a decade.

Paro, modelled on a baby seal, is a companion robot that responds to touch and can make eye contact (photo: UCI UC Irvine)

In 2004, Japanese inventor Dr Takanori Shibata created a 3 kg robot called Paro. The robot is modelled on a baby seal and makes a similar plaintive crying sound. Paro, one of the most widely studied care robots, responds to touch and can make eye contact by detecting the direction from which voices come. It also has a degree of artificial intelligence, including the ability to “learn” behaviour that elicits a positive and empathetic response in the “user” (for instance, being stroked) rather than one that evokes anger, and then to repeat the behaviour that causes the positive response. Some 5 000 Paro robots have been used in more than 30 countries, in therapeutic settings ranging from dementia care to helping earthquake survivors.

Tasks include helping carers as well as patients

Today’s assistive robots can navigate autonomously and carry out a wide range of tasks such as handling, providing assistance with mobility, lifting and bathing in order to reduce the workload of care providers. Their capabilities may include human-robot interaction skills such as face recognition, speech and gestures. These robots are equipped with multiple digital cameras for reading facial expressions and recording the near environment, and stereo microphones and speakers for monitoring and communicating with users. Some models have databases containing photo galleries, music and brain exercises for the elderly.

IEC TC 62: Electrical equipment in medical practice, and its SCs develop International Standards for the electrical equipment and systems and the software used in healthcare. Their work focuses on safety and performance, including data security and confidentiality. There is a joint working group concerned specifically with the safety of the surgical robots and assistive robots used in healthcare.

IEC TC 100: Audio, video and multimedia systems and equipment, has set up a Technical Area, TA 16: Active Assisted Living (AAL), accessibility and user interfaces, to address AAL‑specific issues related to audio, video and multimedia systems and equipment (see article Improving access to multimedia content for those with disabilities in October 2016 e-tech).

Sensors used in care robots include heart rate and blood pressure monitors; sensors to detect changes in motion, audio and scent which could indicate potentially dangerous scenarios for people living alone; range sensors for fall detection; force/torque sensors; light detection and ranging (Lidar) navigation sensors; and red, green and blue image plus depth (RGB-D) sensors for additional navigation data, enabling the robot to perceive objects and people with which it can interact. IEC SC 47E: Discrete semiconductor devices, prepares International Standards for the design, manufacture and use of sensors.

Other IEC TCs involved in standardization work for assistive robots include IEC TC 110: Electronic display devices, and IEC TC 21: Secondary cells and batteries.

As well as care robots, motorized wheelchair robots and exoskeletons offer autonomous motion assistance for the elderly and disabled. Some “robot walkers” are equipped with GPS and wireless Internet connectivity to summon help in an emergency – for instance, a fall – and to enable users’ families to monitor them remotely.

Companion robots

Companion robots are emerging as a specific category. They are designed to act as interfaces that will make it easier for the elderly to enrich their social lives and connect with their families and friends. Typically, they are powered by small electric motors and equipped with high‑definition cameras, voice and facial recognition capabilities, wireless internet connectivity, video‑calling apps, music libraries, memory games and colour-changing LEDs to indicate a device’s “mood”.

An “advanced social companion robot” undergoing trials in California this year is designed to “convey emotion” through different speech tones, sounds, lights and body language. As well as reminding users to take their medication, this robot proactively suggests activities such as reading, going for a walk, playing games or phoning friends. The device uses machine learning to tailor these suggestions to individual preferences.

The European Union and the Japanese government are jointly funding an international research project that will run from 2017 to 2020 to develop “culturally aware robots” to assist with elderly care. Dr Chris Papadopoulos of the University of Bedfordshire in the UK says that elderly users are more likely to accept robots which can “autonomously reconfigure their interactions to match the culture, customs and etiquette of the person they’re caring for”.

Designers of companion robots face issues related to privacy and care‑giving ethics, as well as many technical challenges, not least that robots are currently unable to detect the subtleties of human interactions and therefore to assess people’s moods and feelings.

Analysts see rapid adoption

Healthcare accounts for a substantial sector of the robotics market, primarily in the form of surgical robots. However, the availability of assistive robots for elderly care offering greater functionality and at cheaper prices will see this nascent market segment grow too, particularly in Japan, South Korea, Western Europe and North America.

The consultancy firm Frost & Sullivan predicted in December 2016 that the global market for care assistance and automation robots is expected to achieve rapid adoption, with a Compound Annual Growth Rate (CAGR) of 36% until 2021.

According to Japanese government data, the country’s “care‑bot” market is expected to increase 25‑fold to USD 3,7 billion by 2035.

In the EU, the market for robots and devices assisting elderly people is estimated to reach EUR 13 billion by 2016, according to the Robohub website.

The high cost of assistive robots (currently thousands of dollars each) and the challenges of building safe and certified robotic devices are among the factors restraining market growth.

Access all areas

Japan, a world leader in “eldercare robotics”, has pioneered the development of robots to lift and carry elderly patients and so alleviate the physical strain on care workers.

In addition to talking, understanding speech and navigating autonomously, the Kompaï care robot can keep track of shopping lists, plays music, and work as a videoconference system for users to talk with their doctors, for example (Photo: Robosoft)

At a February 2017 “hackathon” in Singapore on the social use of robotics for elderly healthcare, the winning team proposed an autonomous system using the Segway Robotics platform, Loomo, for transporting wheelchair‑dependent elderly residents in nursing homes and extended-care facilities. The system uses facial recognition algorithms to identify patients, then connects with their wheelchair using a custom-designed electromagnetic coupling, allowing a robot to move patients to and from activities such as meals and medical appointments. This frees up manpower, enabling caregivers to focus on more critical care and medical tasks.

The EU is funding various projects to design robots that can help with specific mobility‑related tasks. They include an intelligent robotic walker that can help someone sit in a chair or assist them as they move around the house.

In the UK, a project known as CHIRON (Care at Home using Intelligent Robotic Omni‑functional Nodes) is developing a system of modular robotic components located in multiple positions around the home which users can adapt to perform different assistive tasks. A key component is a flexible wall‑ or ceiling‑mounted robotic arm-like structure that can provide varying degrees of assistive support, depending on particular needs. The hardware of the robotic arm forms part of an integrated system designed to be connected to other devices and sensors and capable of responding to voice, visual and touch inputs.

Personal care and other assistive robots are becoming increasingly viable ways to complement healthcare technology trends such as smart monitoring systems and mobile applications, thus easing the reliance on human caregivers. The role of the IEC in developing International Standards for the sensors, motors, cameras and other components used in these devices is vital to promote the safety of new products and stimulate market growth.

What do you get when you put together wood and rope? Well according to Plymouth University’s Professor Guido Bugmann: a low-cost, open source, 2 meter tall robot! All buildable for under £2000. The Cheap Arm Project (CHAP) began as an MSc project aimed at developing an affordable mobile robot arm system that could be used by wheelchair users to access daily objects at inaccessible heights or weights (the extreme case being 2 litre bottle).

Now the project has turned open source in the hope of continuing development and gathering more feedback. With the entire hardware and software details available online, with detailed instructions, the team hopes that community members will attempt to construct their own CHAP robot.

While building an entire robot may conventionally seem a complex and expensive undertaking, CHAP stands out with its use of 3D printed parts and wood. In fact, the “under £2000” price tag of required parts is primarily made up of the use six Dynamixel motors, each costing up to £200 and used by the project due to having numerous available during development. With this in mind, future work will look at the use of lower cost motors.

Rather than a robot ‘brain’, CHAP is powered by a human one. To accomplish this, CHAP’s Raspberry Pi was used to host a local web page to enable tele-operation from any connected device, all accessible through a WiFi hotspot also hosted by the Pi. This was an important design choice as it removed the need for platform specific apps and associated costs, simultaneously simplifying deployment and testing.

This was done deliberately to keep the design simple, and to allow users the freedom to interact with their world. Early user-tests discovered that some level of intelligence would be needed to simplify controls. With currently three joints, and three axis available; some steps are needed to automate object interaction (pull requests welcome!).

The next step for CHAP will be refinement of hardware and software; however the very first will be building a community! With full design documents available it is hoped that with support these can be improved and simplified, while simultaneously improving the effectiveness of the software.

Link to the github site can be found here: https://mobile-chap.github.io/Web/

Nearly three years ago, Leka won the Grand Prize at the 2014 Robot Launch competition for their robotic toy set on changing the way children with developmental disorders learn, play and progress. Leka will be the first interactive tool for children with developmental disorders that is available for direct purchase to the public. Designed for use in the home and not limited to a therapist’s office, Leka enables streamlined communication between therapists, parents and children easier, more efficient and more accessible through its monitoring platform. Leka’s co-founder and CEO, Ladislas de Toldi, writes about Leka’s progress since the Robot Launch competition and where the company is headed in the next year.

Since winning the Robot Launch competition in 2014, Leka has made immense progress and is well on it’s way to getting in the hands of exceptional children around the globe.

2016 was a big year for us; Leka was accepted into the 2016 class of the Sprint Accelerator Program, powered by Techstars, in Kansas City, MO. The whole team picked up and moved from Paris, France to the United States for a couple of months to work together as a team and create the best version of Leka possible.

Techstars was for us the opportunity to really test the US Special Education Market. We came to the program with two goals in mind: to build a strong community around our project in Kansas City and the area, and to launch our crowdfunding campaign on Indiegogo.

The program gave us an amazing support system to connect with people in the Autism community in the area and to push ourselves to build the best crowdfunding campaign targeting special education.

We’re incredibly humbled to say we succeeded in both: Kansas City is going to be our home base in the US, thanks to all the partnerships we now have with public schools and organizations.

Near the end of our accelerator program in May 2016, we launched our Indiegogo campaign to raise funds for Leka’s development and manufacturing—and ended up raising more than 150 percent of our total fundraising goal. We had buyers from all over the world including the United States, France, Israel, Australia and Uganda! As of today, we have reached +$145k on Indiegogo with more than 300 units preordered.

In July, the entire Leka team moved back to Paris to finalize the hardware development of Leka and kick off the manufacturing process. Although the journey has been full of challenges, we are thrilled with the progress we have made on Leka and the impact it can make on the lives of children.

This past fall, we partnered with Bourgogne Service Electronics (BSE) for manufacturing. BSE is a French company and we’re working extremely close with them on Leka’s design. Two of our team members, Alex and Gareth, recently worked with BSE to finalize the design and create what we consider to be Leka’s heart—an electronic card. The card allows Leka’s lights, movements and LCD screen to come to life.

We were also able to integrate proximity sensors into Leka, so that it can know where children are touching it, and lead to better analytics and progress monitoring in the future.

We have had quite a few exciting opportunities in the past year at industry events as well! We attended the Techstars alumni conference FounderCon, in Cincinnati, OH, and CES Unveiled in Paris in the Fall. We then had the opportunity to present Leka in front of some amazing industry professionals at the Wall Street Journal’s WSJ.D Live in Laguna Beach, CA. But most exciting was CES in Las Vegas this past January, and the announcements we made at the show.

At CES, we were finally able to unveil our newest industrial-grade prototypes with the autonomous features we’ve been working toward for the past three years. With Leka’s new fully integrated sensors, children can play with the robotic toy on their own, making it much more humanlike and interactive. These new features allow Leka to better help children understand social cues and improve their interpersonal skills.

At CES we also introduced Leka’s full motor integration, vibration and color capabilities, and the digital screen. Leka’s true emotions can finally show!

https://www.youtube.com/watch?v=srHdu7muocM

In the six months between our Indiegogo campaign, and CES Las Vegas, we were able to make immense improvements toward Leka, and pour our hearts into the product we believe will change lives for exception children and their families. We’re currently developing our next industrial prototype so we can make Leka even better, and we’re aiming to begin shipping in Fall 2017. We can’t wait to show you all the final product!

*All photos credit: Leka

About Leka
Leka is a robotic smart toy set on changing the way children with developmental disorders learn, play and progress. Available for direct purchase online through InDemand, Leka is an interactive tool designed to make communication between therapists, parents and children easier, more efficient and more accessible. Working with and adapting to each child’s own needs and abilities, Leka is able to provide vital feedback to parents and therapists on a child’s progress and growth.

Founded in France with more than two years in R&D, the company recently completed its tenure at the 2016 Sprint Accelerators Techstars program and is rapidly growing. Leka expects to begin shipping out units to Indiegogo backers in Fall 2017.

For more information, please visit http://leka.io.

If you liked this article, read more about Leka on Robohub here:

• One year later: Update from Leka, Robot Launch 2014 Grand Winner
• Where are the previous Robot Launch winners now?
• Meet the winners of Robot Launch 2014
• Robotics, artificial intelligence, connected devices in ‘Forbes 30 under 30’

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

You probably know the Sphero robot. It is a small robot with the shape of a ball. In case that you have one, you must know that it is possible to control it using ROS, by installing in your computer the Sphero ROS packages developed by Melonee Wise and connecting to the robot using the bluetooth of the computer.

Now, you can use the ROS Development Studio to create ROS control programs for that robot, testing as you go by using the integrated simulation.

The ROS Development Studio (RDS) provides off-the-shelf a simulation of Sphero with a maze environment. The simulation provides the same interface as the ROS module created by Melonee, so you can test your develop and test the programs on the environment, and once working properly, transfer it to the real robot.

We created the simulation to teach ROS to the students of the Robot Ignite Academy. They have to learn ROS enough to make the Sphero get out of the maze by using odometry and IMU.

Using the simulation

To use the Sphero simulation on RDS go to rds.theconstructsim.com and sign in. If you select the Public simulations, you will quickly identify the Sphero simulation.

Press the red Play button. A new screen will appear giving you details about the simulation and asking you which launch file you want to launch. The main.launch selected by default is the correct one, so just press Run.

After a few seconds the simulation will appear together with the development environment for creating the programs for Sphero and testing them.

On the left hand side you have a notebook containing information about the robot and how to program it with ROS. This notebook contains just some examples, but it can be completed and/or modified at your will. As you can see it is an iPython notebook and follows its standard. So it is up to you to modify it, add new information or else. Remember that any change you do to the notebook will be saved in a simulation in your private area of RDS, so you can come back later and launch it with your modifications.

You must know that the code included in the notebook is directly executable by selecting the cell of the code (do a single click on it) and pressing the small play button at the top of the notebook. This means that, once you press that button, the code will be executed and start controlling the Sphero simulated robot for a few time-steps (remember to have the simulation activated (Play button of the simulation activated) to see the robot move).

On the center area, you can see the IDE. It is the development environment for developing the code. You can browse there all the packages related to the simulation or any other packages that you may create.

On the right hand side, you can see the simulation and beneath it, the shell. The simulation shows the Sphero robot as well as the environment of the maze. On the shell, you can issue commands in the computer that contains the simulation of the robot. For instance, you can use the shell to launch the keyboard controller and move the Sphero around. Try typing the following:

• $ roslaunch sphero_gazebo keyboard_teleop.launch

Now you must be able to move the robot around the maze by pressing some keys of the keyboard (instructions provided on the screen).

You can also launch there Rviz, and then watch the robot, the frames and any other additional information you may want of the robot. Type the following:

• $ rosrun rviz rviz

Then press the Screen red icon located at the bottom-left of the screen (named the graphical tools). A new tab should appear, showing how the Rviz is loading. After a while, you can configure the Rviz to show the information you desire.

There are many ways you can configure the screen to provide more focus to what interests you the most.

To end this post, I would like to indicate that you can download the simulation to your computer at any time, by doing right-click on the directories and selecting Download. You can also clone the The Construct simulations repository to download it (among other simulations available).

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See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

It’s been about 8 weeks since we first introduced Kuri to the world at the Consumer Electronics Show in Las Vegas and we’re incredibly, amazingly, stupendously happy to keep hearing from people about how excited they are about Kuri. We won “Best of CES” nominations and awards from our friends at Engadget, Wired, PC Magazine, and others.

We also heard accolades from people around the world on social media, and even many of our own mothers called to say they heard about our robot on TV.

Since then, we’ve been hard at work, testing Kuri in lots of different homes, fine tuning hardware details and expanding our software capabilities. We’ll be sharing updates, like this, about once a month, letting you know how we’re progressing towards shipping our first robots.

First up, our voice command capabilities are growing. Today, if you say “hey Kuri, I love you”, Kuri responds with an adorable little “I love you too” dance and light show. Or, if it’s time to call it a night we can now say “hey Kuri, go to sleep” and he’ll close his eyes and doze off to dream about whatever robots dream about*.

We’ve also made some big advances in Kuri’s sound and face detection capabilities: he’ll now look toward sounds, and when he sees a face he’ll be able to react with a smile (like we do when we see someone we like), and his eyes will follow you, waiting for your next instruction. This is big step forward making Kuri act alive in ways that are responding to you, and it feels warm and friendly when you see it in person.

Our hardware team has also been covering new territory, redesigning the speaker enclosures that help to project Kuri’s remarkable DJ capabilities, and in a small-but-important detail, updating Kuri’s eyes to be a convex lens shape that reflects light more naturally, making him even more lifelike. They’re more difficult to make, but it’s a detail that matters.

Lastly, we’re excited to also announce that we’ve formalized our partnership with IFTTT, an online service that will make it easy for Kuri to interact with other smart home appliances and devices. We’ll have more on this in future updates, and we can’t wait to show you how smart home connections will make Kuri even more helpful around your home.

Thanks for joining us, we’ll continue to keep you posted on our progress.

* Pretty soon, when his offline mapping and facial recognition training is incorporated, we are pretty sure Kuri will dream about wandering around his home and seeing his family members as he’s consolidating his memories of the day, just like humans do. Right now he’s actually just patiently waiting for our engineers to wake him up again.

This handy video-tutorial course gives an introduction to the Robot Operating System (ROS), including many of the available tools that are commonly used in robotics. With the help of different examples, the tutorials offer a great starting point to learn programming robots. You will learn how to create software including simulation, to interface sensors and actuators, and to integrate control algorithms.

The course consists of a guided tutorial and exercises with increasing level of difficulty working with an autonomous robot. We provide recordings of the lectures and give an introduction to the exercises. From the course website, you can download all the material including exercise sheets and templates, and use the provided Virtual Machine (VM) image to start programming right away.

Objectives:

• ROS architecture: Master nodes, topics, messages, services, parameters and actions
• Console commands: Navigating and analyzing the ROS system and the catkin workspace
• Creating ROS packages: Structure, launch-files, and best practices
• ROS C++ client library (roscpp): Creating your own ROS C++ programs
• Simulating with ROS: Gazebo simulator, robot models (URDF) and simulation environments (SDF)
• Working with visualizations (RViz) and user interface tools (rqt)
• Inside ROS: TF transformation system, time, bags

Course 1:

Course 2:

Course 3:

Course 4:

Download the full presentation here.

P. Fankhauser, D. Jud, M. Wermelinger, M. Hutter, “Programming for Robotics – Introduction to ROS”, ETH Zurich, 2017. DOI: 10.13140/RG.2.2.14140.44161

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Ghost Robotics—a leader in fast and lightweight direct-drive legged robots—announced recently that its Minitaur model has been updated with advanced reactive behaviors for navigating grass, rock, sand, snow and ice fields, urban objects and debris, and vertical terrain.

The latest gaits adapt reactively to unstructured environments to maintain balance, ascend steep inclines up to 35º, climb up to 15cm curb-sized steps, crouch to fit under crawl spaces as low as 27cm, and operate at variable speeds and turning rates. Minitaur’s high-force capabilities enable it to leap up to 40cm onto ledges and across gaps of up to 80cm. Its high control bandwidth allows it to actively balance on two legs, and its high speed operation allows its legs to navigate challenging environments rapidly, whilst reacting to unexpected contact.

“Our primary focus since releasing the Minitaur late last year has been expanding its behaviors to traverse a wide range of terrains and real-world operating scenarios,” said Gavin Kenneally, and Avik De, Co-founders of Ghost Robotics. “In a short time, we have shown that legged robots not only have superior baseline mobility over wheels and tracks in a variety of environments and terrains, but also exhibit a diverse set of behaviors that allow them to easily overcome natural obstacles. We are excited to push the envelope with future capabilities, improved hardware, as well as integrated sensing and autonomy.”

Ghost Robotics is designing next-generation legged robots that they claim are superior to wheeled and tracked autonomous vehicles in real-world field applications. They are also attempting to substantially reduce costs to drive adoption and scalable deployments. Whilst a commercial version of the Ghost Minitaur robot is slated for delivery in the future, the current development platform is in high demand, and has been shipped to many top robotics researchers worldwide (Carnegie Mellon, University of Pennsylvania, University of Washington, U.S. Army Research Labs and Google) for use in a broad range of research and commercialization initiatives.

“We are pleased with our R&D progress towards commercializing the Ghost Minitaur to prove legged robots can surpass the performance of wheel and track UGVs, while keeping the cost model low to support volume adoption—which is certainly not the case with existing bipedal and quadrupedal robot vendors,” said Jiren Parikh, Ghost Robotics, CEO.

In the coming quarters, the company plans to demonstrate further improvements in mobility, built-in manipulation capabilities, integration with more sensors, built-in autonomy for operation with reduced human intervention, as well as increased mechanical robustness and durability for operation in harsh environments. Watch this space.

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• A new quadrupedal robot, the ANYmal
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See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Back pain is one of the leading causes of work absenteeism in the UK, with 8.8 million days lost to work-related muscoskeletal disorders per year. On average, each case causes 16 days of absenteeism, and chronic conditions can cause some absences to become permanent.

But working in a bent forward, back straining posture is unavoidable in a great many professions, like in hospital, agricultural and warehouses environments to name but a few. This regular exposure to demanding postures increases the risk of debilitating pain, which can severely reduce productivity and moral in the workforce.

The Laevo Exoskeleton aims to alleviate this problem. The Laevo is a unique, wearable back-support that aids users working in a bent forward posture or lifting objects. The wearable frame carries part of the upper body weight of the user, thereby decreasing the strain on the lower back and improves the long-term employability of employees.

Video 1: The product

Video 2: See it in action

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Samsung Simband. Image: Jason Dorfman, MIT CSAIL

It’s a fact of nature that a single conversation can be interpreted in very different ways. For people with anxiety or conditions like Asperger’s, this can make social situations extremely stressful. But what if there was a more objective way to measure and understand our interactions?

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) say that they’ve gotten closer to a potential solution: an artificially intelligent wearable system that can predict if a conversation is happy, sad or neutral based on a person’s speech patterns and vitals.

“Imagine if, at the end of a conversation, you could rewind it and see the moments when the people around you felt the most anxious,” says graduate student Tuka Alhanai, who co-authored a related paper with PhD candidate Mohammad Ghassemi that they will present at next week’s Association for the Advancement of Artificial Intelligence (AAAI) conference in San Francisco. “Our work is a step in this direction, suggesting that we may not be that far away from a world where people can have an AI social coach right in their pocket.”

As a participant tells a story, the system can analyze audio, text transcriptions and physiological signals to determine the overall tone of the story with 83 percent accuracy. Using deep-learning techniques, the system can also provide a specific sentiment score for five-second intervals within a conversation.

“As far as we know, this is the first experiment that collects both physical data and speech data in a passive but robust way, even while subjects are having natural, unstructured interactions,” says Ghassemi. “Our results show that it’s possible to classify the emotional tone of conversations in real-time.”

The team is keen to point out that they developed the system with privacy strongly in mind: the algorithm runs locally on a user’s device as a way of protecting personal information. (Alhanai says that a consumer version would obviously need clear protocols for getting consent from the people involved in the conversations.)

How it works

Past studies in this area would often show participants “happy” and “sad” videos, or ask them to artificially act out specific emotive states. But in an effort to elicit more organic emotions, the team instead asked subjects to tell a happy or sad story of their own choosing.

Subjects wore a Samsung Simband, a device that captures high-resolution physiological waveforms to measure features like movement, heart rate, blood pressure, blood flow and skin temperature,. The system also captured audio data and text transcripts to analyze the speaker’s tone, pitch, energy, and vocabulary.

Mohammad Ghassemi and Tuka Alhanai converse with the wearable. Image: Jason Dorfman MIT CSAIL

“The team’s usage of consumer market devices for collecting physiological data and speech data shows how close we are to having such tools in everyday devices,” says Björn Schuller, professor and chair of Complex and Intelligent Systems at the University of Passau in Germany who was not involved in the research. “Technology could soon feel much more emotionally intelligent, or even ‘emotional’ itself.”

After capturing 31 different conversations of several minutes each, the team trained two algorithms on the data: one classified the overall nature of a conversation as either happy or sad, while the second classified each five-second block of every conversation as either positive, negative or neutral.

Alhanai notes that, in traditional neural networks, all features about the data are provided to the algorithm at the base of the network. In contrast, her team found that they could improve performance by organizing different features at the various layers of the network.

“The system picks up on how, for example, the sentiment in the text transcription was more abstract than the raw accelerometer data, says Alhanai. “It’s quite remarkable that a machine could approximate how we humans perceive these interactions, without significant input from us as researchers.”

Results

Indeed, the algorithm’s findings align well with what we humans might expect to observe. For instance, long pauses and a monotonous vocal tones were associated with sadder stories, while more energetic, varied speech patterns were associated with happier ones. In terms of body language, sadder stories were also strongly associated with increased fidgeting and cardiovascular activity, as well as certain postures like putting one’s hands on one’s face.

Graph showing real-time emotion detection. Image: MIT CSAIL

On average, the model could classify the mood of each five-second interval with an accuracy that was approximately 18 percent above chance, and a full 7.5 percent better than existing approaches. In future work, the team hopes to collect data on a much larger scale, potentially using commercial devices like the Apple Watch that would allow them to more easily deploy the system out in the world.

“Our next step is to improve the algorithm’s emotional granularity so it can call out boring, tense, and excited moments with greater accuracy instead of just labeling interactions as ‘positive’ or ‘negative’,” says Alhani. “Developing technology that can take the pulse of human emotions has the potential to dramatically improve how we communicate with each other.”

Click here to download the research paper.

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Pepper, Jibo and Milo make up the first generation of social robots, leading what promises to be a cohort with diverse capabilities and future applications. But what are social robots and what should they be able to do? This article gives an overview of theories that can help us understand social robotics better.

I most like the definition which describes social robots as robots for which social interaction plays a key role. So social skills should be needed by the robot to enable them to perform a function. A survey of socially interactive robots defines some key characteristics that of this type of robot. A social robot should show emotions, have capabilities to converse on an advanced level, understand the mental models of their social partners, form social relationships, make use of natural communication cues, show personality and learn social capabilities.

Understanding Social Robots offers another interesting perspective of what a social robot is: Social robot = robot + social interface

In this definition, the robot has its own purpose outside of the social aspect. Examples of this can be care robots, cleaning robots in our homes, service desk robots at an airport or mall information desk or chef robots in a cafeteria. The social interface is simply a kind of familiar protocol which makes it easy for us to communicate effectively with the robot. Social cues can give us insight into the intention of a robot, for example shifting gaze towards a mop gives a clue that the robot is about to change activity, although they might not have eyes in the classical sense.

These indicators of social capability can be as useful as actual social ability and drivers in the robot. As studies show, children are able to project social capabilities onto simple inanimate objects like a calculator. A puppet becomes an animated social partner during play. In the same way, robots only have to have the appearance of sociability to be effective communicators. An Ethical Evaluation of Human–Robot Relationships confirms this idea. We have a need to belong, which causes us to form emotional connections to artificial beings and to search for meaning in these relationships.

How should social robots look?

Masahiro Mori defined the Uncanny Valley theory in 1970, in a paper on the subject. He describes the effects of robot appearance and robot movement on our affinity to the robot. In general, we seem to prefer robots to look more like humans and less like robots. There is a certain point at which robots look both human-like and robot-like, and it becomes confusing for us to categorise them. This is the Uncanny Valley – where robot appearance looks very human but also looks a bit ‘wrong’, which makes us uncomfortable. If robot appearance gets past that point, and looks more human, likeability goes up dramatically.

In Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley (2) we learn that there is a similar effect between robot appearance and trustworthiness of a robot. Robots that showed more positive emotions were also more likeable. So it seems like more human looking robots would lead to more trust and likeability.

Up to this point, we assume that social robots should be humanoid or robotic. But what other forms can robots take? The robot should at least have a face to give it an identity and make it an individual. Further, with a face, you can indicate attention and imitate the social partner to improve communication. Most non-verbal cues are relayed through the face and creates an expectation of how to engage with the robot.

The appearance of a robot can help set people’s expectations of what they should be capable of, and limit those expectations to some focused functions which can be more easily achieved. For example, a bartender robot can be expected to be able to have a good conversation and serve drinks, take payment, but probably it’s ok if it can only speak one language, as it only has to fit the context it’s in.

In Why Every Robot at CES Looks Alike, we learn that Jibo’s oversized, round head is designed to mimic the proportions of a young animal or human to make it more endearing. It has one eye to prevent it from triggering the Uncanny Valley effect by looking too robotic and human at the same time. Also, appearing too human-like creates the impression that the robot will respond like a human, while they are not yet capable.

Another interesting example is of Robin, a Nao robot being used to teach children with diabetes how to manage their illness (6). The explanation given to the children is that Robin is a toddler. The children use this role to explain any imperfections in Robin’s speech capabilities.

Different levels of social interaction for robots

A survey of socially interactive robots contains some useful concepts in defining levels of social behaviour in robots:

• Socially evocative: Do not show any social capabilities but rely on human tendency to project social capabilities.
• Social interface: Mimic social norms, without actually being driven by them.
• Socially receptive: Understand social input enough to learn by imitation but do not see social contact.
• Sociable: Have social drivers and seek social contact.
• Socially situated: Can function in a social environment and can distinguish between social and non-social entities.
• Socially embedded: Are aware of social norms and patterns.
• Socially intelligent: Show human levels of social understanding and awareness based on models of human cognition.

Clearly, social behaviour is nuanced and complex. But to come back to the previous points, social robots can still make themselves effective without reaching the highest levels of social accomplishment.

Effect of social robots on us

To close, de Graaf poses a thought-provoking question (4):

How will we share our world with these new social technologies and how will a future robot society change who we are, how we act and interact—not only with robots but also with each other?

It seems that we will first and foremost shape robots by our own human social patterns and needs. But we cannot help but be changed as individuals and a society when we finally add a more sophisticated layer of robotic social partners in the future.

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Sophisticated household robots are only just starting to show up in our lives, but all the building blocks for a veritable “Cambrian explosion” of robotics are there, as Gill Pratt described it when he was running the recent DARPA Robotics Challenge. The service robotics industry is emerging, and we will soon be seeing robots of all shapes and sizes making their first forays into our everyday lives.

This is borne out by the recent explosion in robotics and AI funding, which saw robotics investments increase  exponentially over the last five years. While approximately $1 billion was invested in robotics between 2009 and 2014, roughly the same amount was invested in 2015 alone and 2016 is on track to double the total investment again.

According to the CBInsights October 2016 report into “The State of Enterprise: Robotics”, these new investments are largely clustered in autonomous vehicles and the service robotics industry, with strong growth noted in enterprise focused robotics companies.

“Over 50 enterprise-focused robotics companies have raised $259M across 63 deals this year (as of 10/5/2016). These companies are building robots for industrial automation, manufacturing, warehouse automation, and restaurant services, among other tasks.

At the current run-rate, deals to enterprise robotics startups are projected to cross 80 this year, beating last year’s record of 73.

Figure from CB Insights blog “Robotics Startups Funding”

As few as five years ago, the robotics landscape looked simple. While drone and autonomous vehicle technologies were beginning to emerge and cause some excitement, most of the robotics industry was industrial, and the remainder of the landscape was comparatively arid and boring: a few hospital robots, some robot vacuum cleaners, and a few toys and educational robots.

The emergence of the service robotics industry as a serious economic force has taken many people by surprise. It has also made it more difficult to make sense of the robotics landscape, particularly because the new service robotics businesses impact so many markets and applications, making categorization and statistics difficult to obtain, and trends hard to analyze.

Source: Yahoo Finance.

The impact of the internet on the retail sector is a marked example. The demise of physical retail has been hyped since the first dot com bubble, and perhaps this hype has lulled us into a false sense of security. But the huge decline in value of most major US retailers over the past decade is simply shocking. At the same time, robotics offers a potential solution to the pending economic disaster that is threatening the bricks and mortar retail industry. Early signs indicate that robotics is bringing manufacturing back to the US, enabling small batch, just-in-time production in a range of areas from automotive to electronics to biomedical.

Now it seems service robotics solutions in the retail and consumer spaces are offering new ways for brick and mortar companies to likewise maintain their competitive edge. And helping to shape these solutions are a number of Silicon Valley startups featured in this report: Catalia Health, Cleverpet, Bossa Nova, Fetch Robotics, Savioke, Marble, Dispatch, Dishcraft, Momentum Machines, Eatsa, Fellow Robots and Simbe. Indeed, Silicon Valley is at the epicenter of emerging service robotics industry.

Since 2010 Silicon Valley Robotics has been tracking early stage robotics startups and supporting them as they grow. Many of these companies are creating fundamentally new interactions and products, and as they do so, are leveraging the latest business model concepts, including various twists on “Robots as a Service” and “cloud robotics”. With so much new ground being broken, we saw a need to share their stories so that the industry as a whole can learn and grow, too.

Our first report on “Service Robotics Case Studies in Silicon Valley 2015” looked at enterprise robotics companies like Fetch Robotics, Adept, Fellow Robots, and Savioke, who occupied the space between backroom logistics and front-of-house customer service.

The new “Service Robotics Case Studies in Silicon Valley 2016” takes a deeper dive to explore how robotics companies are driving changes in how we interact — not just with technology — but with our pets, our health care providers, and our retail experience.

1. CleverPet (B2C) >> changing how people interact with their pets and delivering data-driven interactions at the far end of the spectrum of the new behavioral robotics.
2. Catalia Health (B2B2C) >> changing how people interact with their medication and life choices, but also how healthcare providers interact with patients >> intelligence built in by experts; allowing for smarter, data-driven interactions.
3. Simbe (B2B) >> allowing retail managers to interact more efficiently with their stock

A clear theme is that each of these robotics startups can unlock data-driven insights with potentially enormous additional business upside by leveraging the ubiquitous connectivity that is being made possible by cloud computing, and more specifically, cloud robotics. Emerging cloud robotics technology enables far more than the simple ability to continuously update and upgrade a physical product, or even to augment the intelligence of that product; it allows robots to become active mobile big data collectors.

Another important theme is how the RaaS or “Robots as a Service” model is maturing, with a range of transactions and applications (e.g. commission-based vs rental-based etc.) to complement the roll out of cloud robotics. Robots are no longer being marketed as simple products for sale, but as sophisticated tools for gaining insights and creating value and driving customer change.

Our second set of case studies and commentaries looks at how accelerators and investors are supporting the drive towards RaaS and finding business models that map robotics technologies into existing business structures, in areas ranging from health to consumer, hospitality to retail.

1. HAX >> helping startups focus on business models via programs like HAX Boost
2. Lemnos Labs >> seeing opportunities for RaaS, working with startups on developing their business plan
3. Comet Labs >> analyzing how intelligent machines can reimagine retail from logistics to customer experience

Every case study and commentary in this report underscores the fundamental importance (and reliance) of human-robot interaction to the service robotics business model — a trend that is sure define the industry well into the future. With so many ‘humans in the loop’ it will become critical that we design robots and businesses that set a high bar for safety, privacy, and ethics. For this reason, we are pleased to announce that Silicon Valley Robotics has just launched a “Good Robot Design Council” with industry expert advisers in an effort to develop design guidelines for the robotics industry that can help fill the ethical gap between standards and laws.

To that same end, our next service robotics reports will focus on self-driving vehicles, agriculture, and other ‘niche’ verticals, with an emphasis on the increasing importance of human-robot interaction, and a look at which aspects of design make good robots and successful businesses.

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For all of us who participated in the Jibo IndieGoGo crowdfunding and are anxiously awaiting delivery – which has been delayed again – this Chinese knock-off came as quite a surprise.

This little Jibo look-alike appears under the brand name Oding with a corresponding website (www.odingbot.com) and a parent company, EDGbot.com. Both companies are registered under a third: HiChina Zhicheng Technology. The odingbot.com website provides a lot of information about their product which is strikingly similar to the content on Jibo’s website

HiChina is registered as a wholesale supplier of electronics, apparel, home & garden, and gifts to customers in China.

Neither of the three sites indicate where to purchase a new Oding nor when they will become available or at what price.

Knock-offs and intellectual property theft

The Oding bot looks a lot like the original Jibo prototype which had a button up front and a slightly wider base than Jibo’s present iteration yet, in an email from Cynthia Breazeal, she affirmed that Odingbot has absolutely no connection with Jibo.

A few years ago Bloomberg Businessweek magazine ran this cover along with a series of stories about stolen technology often copied from plans sent to Chinese contract manufacturers. Those stories appear to be just as true today.

No one should really be surprised. Asian versions of Amazon’s Echo and Google’s Home have been launched and are already being sold in China. Now there’s a Jibo knock-off.

Jibo, the inventor and leader of the pack, just needs to ship. They obviously underestimated what it would take. The cancellation of their developer edition in November is particularly troublesome because no new date was offered. And regarding the consumer edition, for which I am in line waiting, who knows when those will ship.

As Tandy Trower of Hoaloha Robotics, the developer of software and services to support new “socially assistive” robot designs to help people manage day-to-day activities restricted by disease, injury, or aging, said: “This is why I don’t show my robot before its ready.”

Click here to visit The Robot Report.

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British consumers are expected to spend £280 each on gifts over the weeks leading up to Christmas. More than half of these purchases will take place online. Almost a third of people will rely on online reviews to make their buying decisions, although recommendations from friends and family are still the main source of persuasion.

Online shopping is estimated to rise by 24% by the end of this year. However, as consumers are looking for more sensory and immersive shopping experiences, the pressure is on for online retailers to find new ways to excite customers and keep them satisfied – and artificial intelligence (AI) is the new technology they will use. It is allowing businesses to analyse customer behaviour, predict consumer wants and offer tailored customer experiences. In short, AI is expected to make online experiences altogether more personal.

Getting personal

There are already many ways that retailers use AI to interact with their customers. This type of AI is primarily based on learning customer preferences, behaviours and providing tailored recommendations at a mass scale – also referred to as a mass customisation.

The online fashion retailer Stitch Fix gives customers five curated pieces of clothing each month and the customer then decides which pieces to keep. The selection of items is based on customer surveys, Pinterest boards, weather patterns and personal notes to the stylist. From this data, algorithms help the personal stylists to pick out the items the customer is predicted to like the most.

With extensive choice online, retailers try to simplify the buying process. If you are in a shop you are familiar with, browsing is easier. You can glance at a jumper on your way to the toy section, or spot a tea towel down one aisle while spontaneously examining a Star Wars figurine in another.

That dynamic doesn’t work on the internet and so one of the key objectives of using AI in online retail is to assist consumers find what they are looking for and narrow down their potential choice. A new study showed that once consumers have made a decision to purchase within a product category, having a smaller range of potential products to choose from reduces choice overload.

If you are more of a visual shopper, you may like to get your inspiration from Snap Fashion. Using a visual search engine, items from more than 16,000 brands are presented to the consumer based on photos found online or taken on their smart phone. From August 2017, this experience – Snap Fashion InStore – is expected to come to a high street changing room near you.

Chat bots

The next phase of AI in retail will go beyond personalised recommendations to having conversations with customers.

The term “conversational commerce” was coined in 2015 by Chris Messina who leads the development and expansion of Uber’s partner ecosystem. Conversational commerce arises from the convergence of messaging apps, natural language interfaces and brands allowing consumers to chat, message and talk with brands and services with the help of chat bots.

At peer-to-peer online insurance company, Lemonade, customers use the AI bot, Maya, to design their individualised insurance policy. Completed in minutes via the Lemonade conversational app. Customers can also talk to Maya to submit a claim using the in-app video recording feature to describe the incident.

Conversational commerce may move us from being helpless recipients of the work of AI – say, being presented with products we didn’t know we needed – to having direct conversations with AI and becoming active partners in the process. In fact, we may not even be able to tell if we are talking with an AI bot or a human.

Now, few people will buy their mum a Lemonade insurance policy for Christmas, but if you want to get her a new winter jacket, then the outdoor clothing company, The North Face may have the answer. It offers direct interaction between customers and IBM’s Watson-supported natural language questions-and-answers to help identify the most suitable item. Customers respond to a series of questions about how, when and where they expect to use the jacket and particular features that are important to them, for example a pocket that fits the size of your new mobile phone. Based on this information, weather forecasts and delivery requirements, a ranked selection of options is presented.

For running in Snowdonia during December. The North Face/screenshot

This kind of AI-driven personalised shopping is capable of challenging, possibly even replacing, the guidance provided by human in-store sales assistants. It is knowledgeable, fast and able to draw on multiple data points to provide personalised guidance to customers quickly and efficiently. It also goes without saying that AI assistants are less likely to be hungover, bored or tut loudly at your insane questions about a toaster’s bagel feature.

Mass customisation

The use of AI in retail offers opportunities for mass customisation and helps customers to narrow down their choices faster. That has clear benefits for those struggling to grind through the Christmas shopping list. And for companies, it can provide a consistency of service which creates more “sticky” customer experiences online. This is crucial in the face of hyper-competition across all retail sectors.

The trouble is that it also reduces the element of discovery and exploration, which consumers enjoy about the shopping experience, especially during the festive season. It is a streamlining of the buying process, using machine learning and predictive analytics to nudge consumers towards a particular purchase decision.

Consumers’ interactions with brands will become highly personalised when conversational commerce gains traction. These AI systems can be of great help for people looking to solve simple and specific tasks, like buying insurance or gaining technical advice. But for more complex, emotive and subjective buying decisions – like buying gifts for our loved ones – we may still seek that special human touch and personal opinion from friends, family, or even (hungover) sales assistants.

This article was originally published on The Conversation. Read the original article.

Amazon’s Echo sales have exceeded 4 million and they are ramping up to sell 10 million in 2017; Google’s Home has received positive reviews and have just begun selling in large numbers; but SoftBank’s Pepper and Cynthia Breazeal’s Jibo have either failed or are stalled. Why?

The bots: Amazon Echo Alexa vs. Google Home

Amazon’s success with Echo has revealed a consumer acceptance of voice-controlled devices housing virtual digital assistants. Xiaoice, a Microsoft Chinese language bot, has millions of users and can identify photos and carry on playful discussions as if it were a real person. Xiaoice’s acceptance has confirmed that there is a broad user base for these types of bots. What Alexa proved is that there is a growing market of people willing to engage with internet services at home without a screen. That transition, to voice interactions and artificial intelligence, could be a predictor of what’s to come in the near future. Alexa doesn’t need Google. People talk to it and ask it about the weather or recipe ingredients; it looks up things to buy. They search with it. Wait! They search with their Alexa Echo? Google has spent years building intelligent voice assistants for phone and tablets, and now suddenly here’s Amazon  stealing its thunder. Hence the newly launched Google Home

Forbes recently compared Amazon’s $179 Echo to Google’s $129 Home:

“Amazon Echo has a ring of LED lights that tell the user when it’s listening and when it’s processing a request. Users can rotate the top of the device to control volume. There are two buttons on top of Echo: First is an action button for turning off a timer or alarm, or waking up the device for voice commands; the second is a mute button that turns the microphone off so it’s not listening.

Google Home has four colorful LED lights sitting on top that tell the user when it’s listening. It also has a bit more options for physical input: the top of the speaker has a touch surface for playing or pausing audio; changing volume; or starting requests. Like Echo, there is also a mute button.

Amazon Echo is powered by Amazon’s voice assistant, Alexa. Echo wakes up to the word “Alexa” to begin taking your commands. Right off the bat, the device makes it easy to set timers or alerts, ask what the weather is, play music. Echo users can manage all the settings and features in an Alexa app. The app is also where users can enable and browse through so-called Skills — Amazon’s version of an Alexa app.

Google Home is running on Assistant, which is Google’s latest version of its virtual assistant for responding to users’ requests in a conversational manner. Users trigger Google Home with “OK, Google” or “Hey, Google” to start controlling it. It’s able to do the usual — set timers, tell the weather, play a song. But because Google has a lot of information on its users with access to calendars and emails, it can get to know users a lot more intimately than Amazon can right now.

Another important aspect of these two devices is how well they work as a platform for third-parties services and devices. Amazon’s Alexa has more than 3,000 “skills” and can do everything from summoning an Uber to ordering a pizza to turning up the temperature. Google is also creating a specialized developer kit with apps being called “Actions,” and which are separated into two types: Direct Actions and Conversational Actions. Direct Actions are for the kind of tasks that are straight forward — like turn on a light, or play a song on Spotify. Conversational Actions are for a bit more complicated requests like ordering an Uber, where there needs to be some back and forth happening — it needs to know where you want to go and what level of Uber service.”

Amazon’s Echo doesn’t sell in China. Nor does Google’s Home. Here are a few other bots, two of which sell in China:

JD.com, China’s largest online direct sales company, sells a similar product to the Echo and Home devices: the DingDong Smart Speaker. The DingDong Smart Speaker uses the JD+ super app (called “Jingdong Weilian”) to allow full voice control of all products in the JD+ ecosystem.

Baidu, the Chinese telcom giant, is selling Duer, a conversational virtual assistant service. The assistant service provides quick and easy access to Baidu’s various Internet services and engages in a dialogue with users rather than simply being voice-controlled.

Fabriq, a French startup, is a speaker device that sells for $50 and uses Amazon’s own Alexa functionality. With almost all of Alexa’s smarts — everything from music and news to third-party skills, smart home control, and jokes — Fabriq offers plenty of tech appeal in an attractive little package.

“C|Net said: “Fabriq proved to be a capable Alexa gadget. It did a nice job understanding my voice commands, and though it sometimes needed to think a second or two longer than the Echo before pulling up a song I had requested, I came away satisfied with the user-friendly smarts. At just $50, it shows a lot of promise.”

The mobile social companions: Pepper and Jibo

Two notable social robotic ventures are having a different experience than Amazon and Google:

1.   Although SoftBank has sold slightly more than 7,000 Pepper robots to consumers and businesses in Japan and France and still plans to launch in Taiwan, China and the U.S. very soon, their emotion engine – Pepper’s main selling point – will be turned off.

“I’m not sure that being able to read emotions can add to service,” said Morten Paulsen, who covers industrial automation giant Fanuc Corp. as head of Japan research at CLSA Asia-Pacific Markets. “There are several Peppers in my office building, but I don’t see anyone gathering around them anymore. They are basically animated iPads.”

Many people have reported seeing Peppers idle and in corners instead of out front greeting and interacting with people.

2.    Jibo, the much-publicized first product from social robotics pioneer and MIT professor Cynthia Braezeal, has had a series of setbacks and delays including having to refund all non-English-speaking Jibo orders and most recently having to split their initial deliveries into Beta or hold-til-later groups (I’m in the latter). Beta’s are being delivered now so we’ll soon hear from the community how well it performs and meets expectations.

Many other mobile robots have been announced but haven’t come to market just yet. Asus’ Zenbo, at $599, is quite interesting; Buddy from Blue Frog Robotics seems to have run out of money after it got panned in an MIT Technology article; and Future Robots FURo is selling in small numbers as mobile information kiosks.

Bottom line

Can it be that consumers don’t care as much about the mobility aspect as they do about price and conversational interaction? Or is it mismanagement problem, as Bloomberg reporters Pavel Alpeyev and Takashi Amano suggest in their BloombergTechnology report on Pepper and SoftBank?

Paul, a member of the Care-O-bot 4 robot family, has been greeting customers in Saturn-Markt Ingolstadt since the end of October 2016 and directing them towards their desired products. Image: Saturn.

In January 2015, Fraunhofer IPA presented a prototype of the “Care-O-bot 4” service robot. The charming helper is now proving its worth in the real world. “Paul” the robot has been greeting customers in Saturn-Markt Ingolstadt since the end of October 2016 and directing them towards their desired products.

Care-O-bot 4, alias Paul, approaches Saturn customers and welcomes them to the store. If they ask him about a certain product, he accompanies the customer to the department and points them in the direction of the relevant shelf. As he indulges in small talk about the weather, or another subject, Paul turns out to be a most charming contact partner. However, he prefers to leave actual customer service to his human colleagues. Paul is able to call another member of staff for support via “Voice over IP”. Before Paul bids a fond farewell and returns to the store entrance, he still has time to ask for feedback. In this way, he discovers whether customers appreciated the interaction or not. Martin Wild, Chief Digital Officer at Media-Saturn-Holding: “With Paul, we are offering our customers the opportunity to get to know one of the most advanced robots in the world.”

Image: Fraunhofer IPA, Photographer: Rainer Bez (2015)

Modular construction facilitates a wide range of application areas

The interactive robot prototype was originally developed by Fraunhofer IPA as an assistant robot to actively support humans in areas such as the household, hotels, care homes and hospitals. IPA scientists worked together with the design studio Phoenix Design and Schunk over a period of three years to complete the fourth generation of the robot.  While the predecessors of Care-O-bot 4 were used primarily in the development of technological fundamentals from 1989 onwards, the latest version is a modular product family offering elementary commercial solutions for the first time. Fraunhofer IPA is now working with its spin-off company “Unity Robotics” to ensure the solution is suitable for use in various commercial application areas. Saturn is the first customer to make use of the robot platform in real-life scenarios. The project will initially run for six months, with practical findings from customer interactions and employees directly incorporated into the further development of robot technology.

Care-O-bot 4 providing assistance in the kitchen. Image: Phoenix Design 2015

For the assignment with Saturn, the Stuttgart-based scientists supplemented Care-O-bot 4’s software and hardware with additional features. Ulrich Reiser, IPA project manager, explains: “For example, we specified Paul’s navigation, dialog communication and facial expressions. Semvox and Phoenix Design helped implement these changes.” Laser scanners at shin level help with Paul’s orientation. Paul’s front camera and the “Shore” software developed by Fraunhofer IIS allow him to ascertain the mood of the person he is dealing with and express their emotional state. Microphones and cameras for speech and gesture recognition respectively allow Paul to communicate with those around him.

Care-O-bot 4 open for research and industry

Care-O-bot 4 is not only making a positive impression as a retail assistant. With its modular construction and open software interface, the system can be used in many different application areas. It could, for example, conceivably be used as a mobile information kiosk in shops and airports, for pick-up and delivery services in homes and offices, for security applications or as an attraction in a robotics museum. “We retain an interest in ensuring that as many scientists and companies as possible are able to work with the system in order to expand its potential areas of application”, Reiser explains. Within the framework of the Care-O-bot 4 research platform, experts from around the world can further develop the software and hardware components. Together with the spin-off company Unity Robotics, IPA experts are intending to adapt applications to the needs of companies, making Care-O-bot 4 available as a commercial product.

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• Robots that may help you in your silver age

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In this episode, Audrow Nash interviews Hasier Larrea, Founder and CEO of Ori Systems and MSc candidate at the MIT Media Lab, about robotics used to transform personal spaces. Larrea discusses how the world is urbanizing and how new space paradigms are needed to accommodate this shift. He proposes robotic furniture that allows for what is not being used to be hidden, such as a desk or a bed. Larrea discusses the robotic systems, how these systems will be integrated into existing infrastructure, and the future or Ori Systems.

Below is Larrea’s TEDxCambridge talk:

Hasier Larrea
Hasier Larrea is an engineer and designer at the MIT Media Lab. He holds a Bachelors and Masters Degree in Mechanical Engineering. Hasier leads the Architectural Robotics research area at the Media Lab, which focuses on creating a new generation of hyper efficient and responsive urban spaces. His team is developing the robotic tools that allow traditional architectural and furniture elements to transform and intelligently connect to the world around us. His work on the CityHome and CityOffice has been featured in The New York Times, Time, Fast Company, Wired, and TechCrunch among others. His creative and entrepreneurial interests help translate the Lab’s envisioning, inventing, and designing approach into manifesting the ideal smart city from researchers’ minds to the streets of tomorrow.

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• Ori Systems’s homepage
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Source: Halodi Robotics

Our robot, Eve, is built from the ground up using force-control, enabling human-like dexterity and efficiency. We’d like to discuss why we decided to build Eve this way, hopefully offering another approach to robotics outside the factory floor.

A bit of background

Back in 1987, Pål Løken (founder for Halodi Robotics) was attending technical university and witnessed a new generation of industrial robots. People were excited to see cheaper, scaled down commercial robots that were, supposedly, right around the corner. Well, almost 30 years later, and we are still waiting! Pål decided it was time to look into creating a capable, affordable consumer robot, and that’s how we came up with Eve.

When we set out to build Eve, we first looked at the classical approach of harmonic-gears and high-speed motors, as it is an established fact that this works exceedingly well for industrial robots. But we realized this would drive up the cost, and limit controllability and final performance of the robot.

While incremental improvements and miniaturization have been happening, the fundamental actuator mechanics of robotic manipulators has stayed mostly the same for the last 30 years. Even innovative new collaborative robots still use harmonic gears and high-speed motors for actuation.

Here are a few points we needed to consider as we set out to build Eve:

Friction

In gears, one has to choose a balance between backlash and friction and in robotics one typically chooses extremely low backlash to gain good accuracy and repeatability. This results in high friction in the gear itself, and in addition, the friction is scaled by the gear ratio, typically at least 100:1. It is also important to note that friction and backlash is currently not possible to model accurately.

Reflected inertia

When gearing a motor by 100:1, the rotor and shaft need to rotate 100 times faster than the joint. Due to the kinetic energy following the square of the velocity, the inertia get scaled by the square of the gear-ratio, so in this case 10.000. This means even a very light shaft and rotor makes the arm insensitive to external forces.

Backdrivability

Mechanical backdriveability is defined as direct power-flow from the environment to the motors, and full back driveability, therefore, makes the forces reflected from the environment fully controllable. Backdrivability is limited by the friction and reflected inertia.

Eve’s current specifications are:

• No gears
• Runs full torque-control
• Native backdrivable
• Backlash free
• Almost without friction
• Strong as a human (10kg payload)
• Light weight, with the arm weighing only 3kg from the shoulder and down
• Energy efficient due to regenerative braking
• Total of 20DOF with 7DOF arms (excluding hands)
• Whole-body stabilization for fast operation while mobile

Our approach

In traditional robotic control, the lack of backdrivability is used as an advantage. By having a high enough gearing, the joints effectively become highly damped, uncoupled and resistant to external disturbances. This approach then has very good accuracy in position or velocity control but is non-compliant to contact-forces, therefore needing very high accuracy and some passive spring/damper system in the tool.

The natural next step is then force-control, which has seen major advancements the last couple of decades, but has stayed mostly within academia, often only as simulated systems, due to the high friction and backlash keeping robots from applying these controllers efficiently. Force-control works by fully handling the differential equations describing the robot and solving them for close to optimal torques needed for each motor to perform a task. This creates much smoother and more energy efficient motions, and can also take into account contact forces.

It became clear to us that to handle the case of a home service robot, we needed to fulfill our dream of a full force-control robot, requiring almost full backdrivability in the joints.

Could a robot arm that is as strong as a human, be built with a very low transmission ratio?

While a quick survey of available commercial motors said no, most motors today are optimized for medium to high-speed operation. This is due to the efficiency increasing with the rpm as I²R losses become less significant, this assumption does not hold if one looks at the total system efficiency, though. By having a highly geared system, a lot of the energy is lost as friction and backlash, making the total efficiency no way near the motor efficiency. If we could build a motor with the needed torque, our backdrivability would make the power-flow between the environment and our motors almost loss-less, enabling us to reclaim most of the energy through regenerative braking, offsetting the I²R losses. This is especially true in robotics, as most actions start and end at roughly the same potential energy.

Countless hours of books and research papers followed, but in the end, we felt ready to take the next step in motor technology, focusing mainly on torque, not speed. The result was our record-breaking motor technology, managing a torque to weight ratio almost 4x that of any commercially available motor today.

With the torque of these motors available, we started developing our REVO-1, drawing inspiration from the field of haptics, we decided on a cable-driven differential transmission.

This works by counter-tightening a pair of cables for each transfer, we spent a lot of time making sure the geometry of the cables and the drums they wrap on does not result in any distortion to the cable length, this enabled us to tension the cables to the point where there is essentially zero backlash. Also, the near perfect geometry makes sure the cables never translate on the drums, adding close to zero friction and no sound. The final step was making the joints open differentials, driven by differential cables. In addition to compacting the joints and moving even more mass up the kinematic-chain, this enables pairs of motors to share power — making the robot up to twice as strong!

This makes Eve’s friction and inertia low enough that you can move her by gently touching her with a finger. As all the power of the blows is directly transferred to the motors, she can also take almost any shock without sustaining damage!

Since we handle the dynamics fully, we also always know how the arm should behave, any deviations from this is then external force, making the entire arm a 7 degree of freedom force/torque sensor (and potentially haptics device).

The cost question

Eve is a quite complicated machine as a sum of her parts, but the mechanics are mainly machined aluminium and steel with quite liberal tolerances and composite cables attached in smart ways. The E-Ink display, FPGAs, IMUs and other sensors are already mass produced and cheap in volume, moving almost all the cost to motors/drivers/encoders. Since these are developed in-house and we have had a focus on manufacturability from the start, we can produce these surprisingly cheap, making us confident that we can reach our cost goal given sufficient volumes.

As we started testing, we were pleasantly surprised as tests showed the arm using roughly 2-15W to move without payload (without regeneration). Power consumption is crucial to a mobile untethered robot, and the size of batteries is quite significant to cost.

What about today’s collaborative robots, they are also marketed as backdrivable?

There are three common approaches to appearing backdrivable:

1. Simulated by using force sensors to virtually transfer power from the environment,
2. the series-elastic actuator to be compliant with springs,
3. and “low” gear-ratios (typically still 100+) allowing only large external forces to be transferred.

While this works well at low speeds, it cannot mimic the dexterity and speed of the human arm, while interacting with the world.

By being truly backdrivable and low friction our robot is mechanically capable of almost any feat, moving the challenge into our control-software. This makes Eve future-proof, and we hope to push forward the boundaries of dexterity and speed in many years to come, in collaboration with academia and the robotics community.

What’s next for our robot?

We are looking for investors to help build Eve’s cloud-brain and move her from prototype to mass production. With access to a capable and affordable robot, we want to build the ecosystem of Eve’s brain. We plan to make Eve smart enough to know not only how to navigate her surroundings and analyse it, but also noting where all the objects are, and how to properly grasp and interact with them. Using this information to carry out complicated combined tasks will be crowd-sourced to the community through our app store in the cloud. More information at www.halodi.com

We are also currently building version 2 of the Eve prototype, meant for demos and exhibitions, you can follow us for updates along the way!

What would your ideal robot be like? One that can change nappies and tell bedtime stories to your child? Perhaps you’d prefer a butler that can polish silver and mix the perfect cocktail? Or maybe you’d prefer a companion that just happened to be a robot? Certainly, some see robots as a hypothetical future replacement for human carers. But a question roboticists are asking is: how human should these future robot companions be?

A companion robot is one that is capable of providing useful assistance in a socially acceptable manner. This means that a robot companion’s first goal is to assist humans. Robot companions are mainly developed to help people with special needs such as older people, autistic children or the disabled. They usually aim to help in a specific environment: a house, a care home or a hospital.

At the beginning of the 20th century, one of the first pieces of technology designed to help in a household environment was the vacuum cleaner. Since then, technology has transformed the home. Nowadays, we even have a robot that can cook. The chef robot was developed by Moley Robotics, a start-up company that won the 2015 Asia Consumer Electronics Show. The robot is said to be able to cook 2,000 different meals.

Pepper, the latest robot from Aldebaran Robotics, is a good example of a humanoid robot companion. It can provide assistance in making choices, detect human facial expressions and communicate with people. Pepper can adapt its behaviour depending on its perception of a person’s mood, and in this sense we can say that Pepper cares for people. At the moment, only research institutes and Japanese residents can acquire a Pepper robot. The robot costs around £8,710 for a Japanese customer.

Companion robots can take the form of pets, too. Paro is a robotic seal developed to provide comfort to old people. And rather than taking care of you, this robot has to be taken care of. It is how Paro provides emotional support.

Sometimes people get attached to robots that are not actually made for companionship. Take Roomba, for example, the intelligent vacuum cleaner. In their studies, Ja-Young Sung and colleagues from the Georgia Institute of Technology found that people wanted to become tidier in order to allow the vacuum cleaner to run smoothly.

Although many of these robots show some form of initiative and encourage people to interact with them, many are responsive rather than active – in other words, the robot waits for a human request before acting.

Should robots be more ‘human’?

Thanks to progress in Artificial Intelligence and technology, we can now develop more intelligent systems that are capable of acting very much like a human. Last year, a few of them were presented to the public, such as Nadine, the robot receptionist, Yangyang, the singer robot, and Aiko Chihira, the robot that can communicate in sign language.

https://www.youtube.com/watch?v=DydjzhZDdlg

Although the popular and controversial Turing test is used in AI to measure whether a machine is as intelligent as a human, it is a very different thing when it comes to robots, since robots are also expected to act intelligently. There is not yet a standardised test to determinate how human a robot is. It may come in the near future. However, all robotic researchers seem to agree that the robot would have to be able to show some social awareness and personality, and be capable of understanding and recognising people’s speech and expressions.

But do we want robots to have more personality and to be able to take more initiative? Ultimately, to act more like us? Some may argue, yes. If intelligent vacuum cleaners were able to differentiate a sleeping human from objects, for example, at least one unfortunate lady in South Korea wouldn’t have had her hair “eaten” by her new domestic appliance.

But others argue that it is dangerous to give robots too much intelligence. And would it allow them to answer back? We are still at the beginning of research regarding the potential consequences this might have. Indeed, the scientific community is still debating whether a robot can ever have feelings or be self-conscious. Although AI has been able to perform certain tasks extremely skillfully, for example Alpha Go, the community is still a long way from developing an AI which closely resembles the human mind.

https://www.youtube.com/watch?v=3N1Q8oFpX1Y

At present, robot companions are either focused on companionship or on task-execution. Jibo, for example, is a social robot that can talk, order food, remind you of things, or take pictures, while Roomba is an intelligent, but ultimately functional, vacuum cleaner.

Who is in charge?

But it’s about striking the right balance, depending on the job at hand and the person it is working for. Our most recent study, Who is in charge? Sense of control and Robot anxiety in Human Robot Interaction, showed that the more controlling and anxious about robots a person is, the more initiative they expect the robot to show and the more willing they are to delegate tasks to it. The research focused specifically on what level of initiative people preferred their robot companion to have when executing a cleaning task.

Participants could choose between manually turning on the cleaning robot themselves, having their robot companion turn on the cleaning robot remotely when instructed, or having the robot companion turn on the cleaning robot when it noticed that cleaning needed to be done. It was found that most people wanted their robot companion to execute the task without being asked.

This paradoxical result may be explained by the fact that people are now more used to technology – from computers and smartphones to smartwatches and intelligent home appliances – acting semi-autonomously. Smart companion robots are just the next step in the long evolution of our relationship with technology.

In the future, it is likely that we will see more domestic robot companions that can be customised to people’s individual preferences. And we will be able to shop for them as we now shop for vacuum cleaners and phones. Ultimately, it seems, there will be a robot for everyone.

This article was originally published on The Conversation. Read the original article.

If you liked this article, you may also want to read:

• Robots that may help you in your silver age
• Caring for robots: How assistive robotics may change our homes
• 2016 will be a pivotal year for social robots
• Architectural robots: The shape of the robots that will shape your home
• Japanese telcos vie for share in consumer robot-as-a-service business
• Robot caregivers: How much interaction with a robot is socially acceptable?
• Driven by care needs, will it be the booming senior population that spurs wider acceptance of robots?

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

iRobot recently divested its defense division so that it could focus on consumer and mobility products. Red Mountain Capital, a hedge fund that owns ~6% of iRobot stock wants to place two people on the iRobot board to effect some change.

Proxy Fight

Red Mountain Capital has forced iRobot into a battle over management direction, a fight described in detail in a story by Jon Chesto of The Boston Globe: IRobot CEO faces what could be his biggest test: a heated proxy battle over company’s future.

Red Mountain considers itself to be an activist shareholder – and wants to play a more direct role in how iRobot is run, how iRobot funds are allocated to R&D, how expenses are controlled, and how much is returned to shareholders. iRobot thinks it is successfully handling strategic planning, product development, return on equity, and prudent manufacturing operations without adding extra financial advice from non-industry people to the mix.

The Globe article, describing iRobot's planning for the future, describes iRobot's Venture Group and their investments in future companies within the mobility, consumer and home marketplaces – all areas where iRobot has expertise. One investment is particularly interesting and offers the prospect of much growth for iRobot as well as the startup: 6 River Systems, a Massachusetts startup comprised of ex-Kiva Systems execs. 6 River is providing a mobile robot solution for material handling in warehouses, factories and distribution centers. It's a big marketplace particularly since Amazon has taken the Kiva technology in-house with the consequence that new vendors (such as 6 River) are scrambling to fill the void.

In the Boston Globe article I was quoted as summarizing the iRobot / Red Mountain proxy fight as follows:

“From time to time, any company really can use a shake-up. But you can shake up the company [iRobot] just by talking to Colin,” Tobe said. “You don’t need to put two hedge-fund, money-type people on the board.”

Global Home Vacuum Market

From the chart above one can see that iRobot's share of the global robot floor cleaning market is 63% of units and 40% of revenue, and shows year-over-year gains of 8.3% for units and 9.3% for revenue.

The robot segment of the overall home vacuum cleaner market has also been growing. Colin Angle, iRobot co-founder, Chairman and CEO, used this chart in a 2014 presentation:

Thus one can see that robotic vacuum sales are becoming more popular but at a lower growth rate than the general vacuum market growth rate. And from Angle's presentation slide, it's clear that although iRobot has a goodly share of the market, their revenue could be higher and their overall capture rate is going down instead of up.

Conflicting Forecasts

The following three research reports vary widely but all show double-digit growth within the robotic sector of the global home vacuum market.

• Global Industry Analysts, a San Jose, CA research firm, in a 2014 report, forecasted the global market for household vacuum cleaners to reach $11.4 billion and 115.7 million units by 2020. 
• Grand View Research, a San Francisco research company, in a 2015 report, says that the global household vacuum cleaner market size was valued at $11.2 billion in 2014 and is expected to grow at a 4.9% compounded annual growth rate (CAGR) through 2022. Grand View also estimates that the robot vacuum segment will grow at a CAGR of 11.4% over the forecast period.
• ABI Research, in a 2015 report on Robotic Home Care predicted that the home care/lawn care robotics market will surpass US$2.9 billion by 2019, up from US$1.2B in 2014 and that approximately 7M robotic home care/lawn care products will be sold in 2019, up from 3.4M in 2014, representing a CAGR of 15.6%.

Transcript below.

In this episode, Audrow Nash interviews Silas Adekunle, Co-founder and CEO of Reach Robotics. They speak about Reach Robotics’ first product, Mecha Monsters: legged, gaming robots that are controlled by a smartphone.

Through Mecha Monsters, Reach Robotics is attempting to connect the physical and digital components of the gaming world. Adekunle also discusses the startup process, including technology accelerators.

Below is a video where Silas reveals Mecha Monsters.

https://youtu.be/D7uHQMB6WE0

And an image of a Mecha Monster.

Silas Adekunle

Silas Adekunle is the Co-founder and CEO of Reach Robotics, a company developing intelligent gaming robots. He established Reach Robotics while still an undergraduate at the University of the West of England, UK. Before Reach Robotics, Silas managed a “Robotics in schools” program in partnership with UWE, the UK government, and HP for 4 years, leading a team of engineers going to schools to develop the interest of young students in STEM through robotics. As a robotics engineering graduate and avid gamer, Silas’ goal is to make robotics more accessible to both young and old through play.

Links:

• Download mp3 (20.1 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Reach Robotics’ Website

Transcript
This transcript has been edited for clarity.

Audrow Nash: Hi, welcome to Robots Podcast. Can you introduce yourself to our listeners?

Silas Adekunle: I’m Silas Adekunle, CEO and co-founder of Reach Robotics. I’m from the UK, but we’re currently in San Diego, where we’ve just taken part in the Qualcomm Robotics Accelerator, powered by Techstars.

Audrow Nash: Great! Tell me a bit about Reach Robotics.

Silas Adekunle: Reach Robotics is developing the world’s first intelligent gaming robots. I don’t know how many people are familiar with the movie Big Hero 6, by Disney. There’s an underground battle scene where the kid brings out a robot. It’s like everything you fantasized as a kid — having a real robot companion that can battle, and upgrade. It’s an entertainment consumer product, but the vision’s a lot more than that.

Audrow Nash: What do they look like? They’re called MechaMonsters, correct?

Silas Adekunle: Yes, they’re called MechaMonsters. The branding is about to change, we’ve spent a lot of time in the accelerator so there is a lot of new stuff coming. They look like four-legged robots, quadrapeds, who are well-articulated so they move fluidly. They’ve got weapons on their backs, or weapon ports, and shields, like something out of a sci-fi movie.
Audrow Nash: What are weapon ports? Can you attach new weapons, do they actually do anything?

Silas Adekunle: What we’re doing is supplying game play mechanics. You start with your robot at level one. The more you train by battling other players, or by engaging in activities, the stronger they become.

That means you can start to add on weapons, shields. They don’t just change the way your robot looks. You can tailor your MechaMonsters any way you want, and it also improves your performance in battles. They’ve got electronics that allows the robot to know what functionality to add to the robot itself.

Audrow Nash: How would you describe the weapons? Is it a click on piece that has electronics the robot registers?

Silas Adekunle: Yeah, that’s right. So each weapon has an IDE that plugs into the robot, where we plan to add different types, different levels of functionalities. Weapons will be moving parts, so a bit more premium. Weapons by themselves are little, but look awesome. Each weapon, or add on as we call them, has a piece of electronics that has an ID for the robot.

Audrow Nash:
Are shields entirely in the user’s imagination? Or does it register on the smart phone controller?

Silas Adekunle: When you put the shield on, it clips to the leg of the robot. So it’s a physical item that clips on.

There are ports on the leg of the robot and on the back. We call them hard points. These are all the game play mechanics or terminology for the MechaMonster world we haven’t put out yet, because we’ve been trying to get the foundation right. Over the next few months we’ll be more engaging with early adopters so we know exactly what we put into market next year.

Audrow Nash: What does a battle look like with two users controlling the MechaBox?

Silas Adekunle: You’ll be able to knock your opponents over for higher damage. It’s interactive game play, the way you’re trying to use the world around you to your advantage, hide behind the table leg, things like that. You try and outsmart your opponent. Because the robots are maneuverable we’re focusing on the strategy of the game play. For example, there are skills where you can stun your opponent’s robots for a few seconds. The robot will just stay there and not be able to move because they need five second to wait. That gives you the opportunity to get behind your opponent.

It’s one of those things that’s better experienced than described, sorry to say!

Audrow Nash: What kind of sensors are on the robot? Do they interact in game play or battle?

Silas Adekunle: We’ve got sensors for the robot state, in itself. We have an IMU [Inertia Measurement Unit] in there so that the robot knows its orientation, a sense of where it is. We have infrared images, so that robots know distance from each other and orientation. Those are the metrics that plug into the role, the game play.

Silas Adekunle: For the infrared emitters, do you just have one that emits in all directions, and then so the robots can tell their relative distance from each other? Typically, an infrared LED it’s very directional.

Audrow Nash: Which direction are the infrared emitters and receivers? Are they in the front of the robot?

Silas Adekunle: The four sides of the robot.

Audrow Nash: Are you changing the way they emit based on the side? A sort of light signal that you can detect to tell if the robot is turned?

Silas Adekunle: Exactly. You brought different IDs, so to say, for each side so you know that I’m reading 1 for front, 4 for the back.

Audrow Nash: That’s how you make sure that if the robot attacks and it’s facing the wrong way that it doesn’t register. For an attack to hit, the robots have to be within a certain distance and facing the correct direction?
Silas Adekunle: Exactly. There’re different types of attacks, and this will be for the people that want to get into the game play. For example there are some attacks that don’t care about direction. In game play stuff like aerial effects attacks.

Audrow Nash: Like a ground smash?

Silas Adekunle: Exactly. It doesn’t matter where your opponent is, as long as they are within a certain distance, the orientation doesn’t matter.

Audrow Nash: If I was a slick kid, could I cheat by covering up my infrared detectors in certain directions so my opponent couldn’t hit me from the side or something?

Silas Adekunle: Yeah, you could, but that would make you a spoil-sport. Once we start to get into the game-play testing we’ll have our own methods of making sure that people don’t cheat too much, but at the end of the day in every game you have the hackers and the people that will out-smart everyone else. We like that, people are going to be able to hack this stuff to bits, and we want that. We just hope that our customers will be fair players and not annoy their friends too much and be too much of a spoil-sport.

Audrow Nash: Are you making this open to the development community? Do you see research labs using it?

Silas Adekunle: Definitely, it’s part of the story of the company. This all started because I was eventually going into schools, teaching kids robotics, and it’s something that we love very much, and all of us engineers, we want that. We were careful how we wrote it out to make sure people don’t break their robots, but it’s something that’s part of the plan for us, to have versions that people can just take apart and use for development itself.

Audrow Nash: For the hackers, will it have its own operating system on it, like its own little Linux I can pull up?

Silas Adekunle: We’re considering it, we’re still debating exactly how we’re going to do it. I don’t want to make any promises. We want it to be accessible and easy to use.

Audrow Nash: The primary focus for MechaMonsters is to be put in the toy industry?

Silas Adekunle: Yeah, the entertainment industry. We call ourselves a robotics gaming company for a reason, because we think the amount of work that’s going into this product and the experience that we’re putting together it puts it with Skylanders.

Audrow Nash: What is that?

Silas Adekunle: Skylanders is a game, by Activision, where you can buy figurines and use them to unlock characters in a video game. It’s a product that straddled the physical and virtual world, so the lines are starting to blur. For the product in the next 5 years, the kinds of products that are going to be on market it’s going to be hard to define them as toys or games. We find our-self in this spot where we’re halfway between the toy, the intended market, and half of it’s in the gaming market. To kick off we are releasing this product for entertainment.

Audrow Nash: What kind of people do you see buying this? Is it for children?

Silas Adekunle: From interacting with our customers we’ve had interest from children all the way up to adults. These are people with disposable income that are getting nostalgic, they’ve always dreamt of this as a kid and we’re now giving it to them. We’re lucky because we have a product that appeals to so many people: Boys, girls, adults, people that are very techy to people who just want to see their robot beat the crap out of another robot. We consider ourselves to be a consumer product, where the kind of people that will buy it initially will be tech-savvy people until the brand takes off and becomes a general market item.

Audrow Nash: Tech-savvy people to begin with, not kids?

Silas Adekunle: As part of our go-to-market plan we have a campaign in mind that we’re going to launch, and the kind of people online that will have this campaign are going to be people that have access to the internet and things like that. Maybe some parents that want to buy it for their kids, but in the short term it’s going to be someone that’s no Kickstarter for example, that would be able to have initial access to it.

There’s a reason for that. This is a very complex product, a very unique product, and we want to do it justice. We want to give access to people that will be patient enough to give us critical feedback. This is what we like about the product, this is what we don’t like about the product, so that when it starts to reach mass market the people are getting the best experience that we can offer them.

Audrow Nash: Initially, it’s for just testing and feedback so you can refine it.

Silas Adekunle: Exactly.

Audrow Nash: How did you pick your market in the beginning?

Silas Adekunle: It’s a route that’s worked well for other companies so far. It’s not particularly Kickstarter people, it’s where do you find your early adopters. When you’re taking a product to market, how do I get this product end goal?

Audrow Nash: Kickstarter, IndieGoGo Campaign, sites like this, people that are looking for products, or on Reddit. How did you identify your audience?

Silas Adekunle: By taking the product out there and getting feedback. We actually did some testing online ourselves, we took the product out, for example spent a whole day at a Comic-Con in San Diego, we put our product on the internet across different websites, just looking at what people think about this. Did some preliminary research, as much as a small startup can do, and that was how we identified who the kind of people are that would initially be the right early adopter for this, who could give the right feedback.

Audrow Nash: What is a tech startup accelerator? How has this changed in the startup accelerator? I assume that it’s gone through more refinement of who your target audience will be.

Silas Adekunle: A tech startup accelerator is exactly what it sounds like. The company goes in and they must accelerate you to the next stage. That’s different for each company. The accelerator that we were part of, we had companies that just at the idea stage, we had companies that were at the market validation stage, we had companies that were at the growth stage. It’s tailored depending on which accelerator you go into.

There are some that are hardware focused, ours was hardware focused, and it’s there for each company to take them from stage one and rapidly get them to the next stage for them. For us we need a bit of work on the marketing side of things and quite a bit of work on the product development side of things as well. You’re looking at what market you should be aiming for, not just in the short term but the grand vision for the company, and how do we create a product that addresses that.

Audrow Nash: How did that develop? How did you choose for the early adopters in the tech field, and how was that affected by the tech startup accelerator.

Silas Adekunle: The great thing about accelerator was the network you get out of it. You can talk to founders of other robotics companies and what they’d done to get to where they are today. That was how we figured out our strategy, just talking to 4 or 5 past founders. We discovered that a pattern occurred if you’re a consumer product. What worked best is to put it out there to early adopters, and the best channel to reach them on today is by online; platforms like Kickstarter or IndieGoGo are there to make that easier for you. Then, when you reach your early adopters and you have your direct sales and gotten your feedback, then you start to get into your retail channels. It’s really talking to other founders and identifying what strategy worked for them and looking at how we could apply it to our products as well.

Audrow Nash: My impression would be that the early adopters that you find on these websites would be a much smaller market than say the toy industry. How are you guys maintaining funding until you tap into a larger market? Do you seek venture capitalists? They’ve invested in you?

Silas Adekunle: Yeah, we raised money from investors that share our vision and like what we’re working on. Just like any startup, we raise and then use that money to develop before you get to market. The money you raise is to fill that gap before you’re self-sustainable.

Audrow Nash: Going back to MechaMonsters, there has been previous robotic battle toys. One that I had when I was a kid was called Rumble Bots, and the idea with Rumble Bots was they were little remote controlled robots, you didn’t use a smart phone, but you loaded in different behaviors, attacks, that kind of thing by scanning in cards to them. They would read the cards, and then after they were all loaded the devices would battle. This company went bankrupt. What makes MechaMonsters different than other companies that maybe didn’t do as well?

Silas Adekunle: [00:13:00] It’s a question we get asked all the time because battle robots is an idea that people have had. It’s recurring; you’ve got Battle Bots in the US, Robots in the UK, Real Steel and other movies. It’s something people want. It took us awhile as well to figure out exactly what’s different about us, or why we’re going to succeed.

It boils down to creating a battle robot, and there are loads of companies that have tried this in the past. What you’re trying to do is create an experience. We’ve looked at it and said, “Okay, we’re going to create this experience of people being able to battle each other. How exactly are we going to make it the best experience that they can get?” We’ve taken that approach to everything that we’ve done. Initially to kick this off we took a lot of advice from people in the toy industry, and then took a lot of advice from people in the other industries.

Sorry, it’s a bit of a lengthy answer.

Audrow Nash: That’s fine.

Silas Adekunle: The first thing to create a successful product is that there has to be 3 elements: Competition, collectability, and customization. We have all of the elements in it.

Audrow Nash: Where do you get these 3 from?

Silas Adekunle: These were recurring answers from toy industry people. If you look at products that have been successful, apart from the massive amount of marketing budget that were behind them, fundamentally they had these parts.

Skylander, Pokemon, had these if we’re looking at purely the toy industry. When it comes to battle robots, this is stuff that captures people’s imagination. When people say, “I’m gonna buy a battle, or I want a battle robot,” they’re not thinking I want a plastic toy or something, they’re thinking, “I want that epic, awesome robot that I saw in this movie I watched yesterday.” To really deliver that experience we’ve had to focus a lot on the hardware.

For example the Rumble Bots, I think they’re a price about $40, looking at their costs that means their building materials must have been something like $10. This is a while back, right, so looking at the type of technology that was available for that price at the time, the type of components you could get I don’t imagine would be very good.

Audrow Nash: Yeah, and they were before the cell phone boom so, I mean, you get your IMU on your chip then.

Silas Adekunle: We’ve had to think a lot about the hardware. Our robot is very complex, it has 12 degrees of freedom all together.

Audrow Nash: How many?

Silas Adekunle: 12 degrees, so 3 per leg. That means you can make it create awesome moves just like you’d see in a movie. Then, we had to think about what happens if the leg of a robot breaks, which is why the robots are modular. Things we haven’t really announced yet because it’s early in development but will work soon.

We’ve had a massive think, and it’s user experience driven, so we’re creating an experience, we’ve got to create the hardware to deliver that experience. I think that’s what’s different about us, the timing is right and the approach we’ve taken is right. The reaction and the feedback we’ve been getting points that way. When we get to market there’s going to be a lot of stuff that we’ll get wrong at the start, and that’s why we appreciate the feedback that we receive to tailor it.

All of us on the team, we’re gamers, we’re engineers, so we’re not going to put something crappy product out there, that’s what we hope anyway. We’re looking at it from the point of view of, “How are we going to create the best user experience possible,” and that’s what’s driven us so far.

Audrow Nash: What channels are you putting in place for feedback?

Silas Adekunle: We’ve got emails, people can send loads of emails, the accelerator, we’ve sent out some surveys to get feedback from customers. We sent out surveys to about 1,000 people.

Audrow Nash: What would you plan once you unveil it for the early adopters’ audience?

Silas Adekunle: What we plan after that? We sent out our surveys to get feedback, and we had some open-ended questions, non-leading questions. These are questions to confirm our hypothesis or to challenge our hypothesis. You always challenge a hypothesis. Then we’ve gone to live events with the people that we think are our target market, for example as I mentioned Comic-Con here at San Diego.

In the long run when the product is out there, we’re going to be doing a lot of face to face interactions. Once we’re at that state that we can start beta testing, there is going to be lots of invites to get people to try this and give us feedback.

The great thing about this product is that it’s digital in every sense of the word, you’re controlling it from a phone. That means we can look at how people are using the product and get instantaneous feedback, which I think is great for the time we’re launching this product, compared to Rumble Bots for example. We can know exactly how people want to play with this robot, what they do with it, and exactly what they don’t like about it and change it on the fly, so to say.

Audrow Nash: It connects to WiFi? It’s Bluetooth that you’re connecting the robot, but can you send updates over Bluetooth?

Silas Adekunle: Not in itself.

Audrow Nash: It has to connect to WiFi somehow?

Silas Adekunle: This is in the software itself. We’ll have a control infrastructure in there for how you control the robot from the app, so because the app is connected to the internet.

Audrow Nash: The brains of the robot are in the smartphone, it’s just a big actuator that you buy as the robot that receives this message. It’s like Fly By Wire for EJ Kumar’s Lab.

Silas Adekunle: There’s leverage in the power of the smartphone, I think, as part of the game place experience itself.

Audrow Nash: Because the brains of the robot are on the smartphone, you’re controlling what it does from the smartphone? You can add new behaviors to the smartphone to make it do new things, and that’s how you can update it, by updating your app or however you’re running your backend?

Silas Adekunle: Exactly. That’s an idea about how it works.

Audrow Nash: It’s a neat way of controlling it. Going back to the startup accelerator, what was it like?

Silas Adekunle: Hectic, I need to sleep. It was a very intense period.

Audrow Nash: Just for context, you’re at the end of it?

Silas Adekunle: Yes, we graduated last week. That finished last week. It was a very intense 4 months for everyone on the team and all the other companies that where here. You’ve got a target that you’re working towards, there’s demo at the end of it with a fixed date. What you show at the end is up to you, but it’s an opportunity to accelerate it or rapidly take your company to the next level.

Audrow Nash: What are these levels?

Silas Adekunle: For example, for a pre-seed company it would be to raise your seed round so that you can get to market faster.

Audrow Nash: That’s get enough founding?

Silas Adekunle: For other companies it’s to, by demo day, have 100 letters of intent that they’re going to use over at the B2B company.

Audrow Nash: It’s progressing to the next levels, so the next level of the company towards bringing a product to market and being successful in market?

Silas Adekunle: Everyone goes into that territory with this mindset of, “We’ve got 4 months and this our deadline,” and you work extremely hard to make that happen. This is all the while trying to take advantage of the networking opportunities that you’re getting. We met a lot of world class people, founders like the founders of Sphero, founders of other robotics companies like PetRo Robotics, all these people that have lots of success stories that you hope one day want to be like them, you get to meet them. You take in all these feedback, it’s just a massive boiler pot of feedback, development, business development, product development, everything all in one. It’s a very intense period. It’s fun at the same time.

Audrow Nash: Before you decided to be in the startup accelerator, what were the pros and cons of being in a startup accelerator you considered?

Silas Adekunle: Depending on where you are. For us, we had to move out of the UK to the US for it. That was a pro because the weather in the UK sucks so no one complains about going to sunny San Diego, but you’re leaving family behind. It’s all part of the startup roller coaster ride, ups and downs, emotions and all that. You’re leaving a well-known establishment or infrastructure that you have behind, something where you don’t know. In terms of the cons, there aren’t that many cons.

Audrow Nash: The pros you mean? Or the cons?

Silas Adekunle: Yeah, there aren’t many cons. The only con I would think is you’re leaving a well-established infrastructure behind for something unknown. Going into it we were all super excited. The pros way outweigh the cons, it’s an opportunity to take your company to the next level, it’s an opportunity to meet world-class mentors, it’s an opportunity to meet other founders, it’s an opportunity to really spend a whole intensive period with your team and get to know them better, and everyone is focused on the same goal and same target. The pros way outweigh the cons if you have a startup company.

There are different levels of accelerators, Techstars is a fantastic one. If you have an opportunity to apply to Techstars accelerator, take it.

Audrow Nash: It sounds like you’ve learned a lot from this accelerator. What would you say is the biggest lesson you learned?

Silas Adekunle: We learned a lot. This might not be the biggest lesson learned because I haven’t had time to reflect, you should take time at the end of accelerator just to sit somewhere and gather your thoughts.

We learned a lot of great lessons. No matter how big the companies are, at the end of the day it comes down to people: people are what make companies successful. Regardless of the product, idea, market, which are all important, it’s the team that’s most important.
At the very early stages of the company it’s important to put together the right team and treat people you find right because they make or break your company.

Audrow Nash: Would you talk a bit about the long term goals of Reach Robotics?

Silas Adekunle: To take over the world.

Audrow Nash: Naturally.

Silas Adekunle: Naturally, as a robotics company what else do you do? For us the main thing we want is to focus on consumer entertainment, then we see an opportunity for us in education. If we want to shorten it, robotics and entertainment, it should be followed by Reach Robotics.

For us it’s really about getting the product to market, receiving feedback, and always creating something that delivers a great user experience. I think in the toy industry as opposed to the consumer tech industry, there isn’t a lot of brand loyalty because you can just release a new brand with one hit product each year, and then create another one next year.

There isn’t really a name that sticks around as opposed to Samsung, Apple, and all these giants in other industry, in tech. We want to change that and really focus on the user experience we’re developing and create a lasting company, as opposed to a one-hit-wonder.

Audrow Nash: What are some of your ideas on doing that, creating a strong brand?

Silas Adekunle: Community is important. Again, we can’t really dive into the products, but what we want people to be able to do is to create skills for their robots and share them online. If I create a new battle skill I can share it with my friends, so there’s a community aspect. If you design a shield or a weapon for your robot, then you’d like to 3D print, we want that infrastructure in place to provide. We want to focus on brand and community as part of our key defining features for the company.

Audrow Nash: How useful would you say was your university experience, engineering in robotics background, for your current endeavor with Reach Robotics?

Silas Adekunle: Make-or-break, so to say. You can’t go into robotics without having a background in robotics, you wouldn’t know what you were doing at least to get off the ground. I still don’t know what I’m doing, but I knew enough to get off the ground. There’s always new technology coming out and you’re picking it up, but the foundation is important and university education gave me that foundation to have a broad understanding of the robotics space.

There were lots of opportunity for networking in the university. When I was in university I was in this stuff, I think it’s Steam here, we call it Stem in the UK, that was an opportunity to network with other people that were interested in Steam, and it was a university network. I actually found my co-founders though the robotics lab where I was based. I can’t picture being here without the path I’ve taken.

Audrow Nash: Why did you choose to start the company and doing this now immediately after your bachelors, rather than doing more education? How did you make this decision?

Silas Adekunle: Impatience, I suppose. I started the company during my bachelors, during my studies. Whenever you’ve got an itch, you’re not going to wait for anyone you just do it and figure it out along the way.

It’s always been that mentality: we’ll do it live. You get on the road and we’ll just do it live, we’ll figure it out, otherwise you wait yourself to death. It’s never the perfect time and I found that no matter how uncertain you are about something if you just go out there and do it, along the way you’ll find the right people. Even if they don’t have the answer they will point you the right direction towards the answer.

There’s never a perfect time, just go for it, and that was what I did.

Audrow Nash: Thanks for the interview!

Source: Fraunhofer IPA/photo: Jens Kilian

By 2020, a quarter of Europeans will be over 60. In their silver age, many would like to stay in their homes and will require care from family or social workers. Unfortunately, the number of caregivers is diminishing year-after-year due to shifting demographics and an increase in working families. This leads to a ‘care deficit’ that poses a major challenge to most European societies. And today’s social workers are often hard pressed, wishing they had more time to connect with the people they care for, rather than the minuted dance of tasks that need to be done. It’s also hard physical work requiring workers to bend over up to 1300 times per shift .

It is like you are part of a machine. You’ve got to be here at this time and you’ve got to finish at this time. [. . .] It’s all down to minutes. – Peter, care worker

It’s an area that is ripe for innovation, enabling both day to day care, and more meaningful human interactions.

So, how can robotics technology help as you grow older?

Connecting you with loved ones
Telepresence robots allow care workers and family to drop by your house remotely. There is no need to pick up a phone, or start a computer. The robot, essentially a videoconference system on wheels, will drive up to you and initiate a conversation. It’s the modern day equivalent of a knock on the door. The idea is not to replace in person visits, but to allow them to happen more frequently, and at the times that matter most. Imagine having your daughter drop by – albeit sometimes virtually – multiple times a day, or being able to ask for help when needed.

Giraff, a telepresence robot developed through two European Projects (ExCITE and Giraff+) is currently undergoing tests in homes across Europe and is already available for purchase.

Helping you get around
Reduced mobility is one of the main causes for people joining a care home. Whether it’s walking, lifting everyday objects, eating, bathing, or getting up from a chair or bed.

An estimated 9 million people in the EU need help getting out of bed. – Multi-Annual Roadmap for Robotics

Focus has been on making robots that can help with specific mobility-related tasks. The MOBOT project for example is currently developing an intelligent robotic walker that could help you sit down in a chair, or assist as you move around your house.

MOBOT Project

LEA from Robot Care Systems is also a carebot disguised as a stroller that may help you get out of bed, walk, or hold a cup. LEA also knows about your daily routine, and can sense if you’re not taking medication, eating, or drinking.
And Company Besticinc, founded by Sten Hemmingsson who was disabled by Polio, looks at how robots can help you eat.

It is extremely important for a person’s integrity that you’re able to eat independently. – Sten Hemmingsson

Rather than buy a robot for your home, you may instead be wearing it as an exoskeleton to help with everyday movements. The AXO-SUIT project is providing inroads into developing an exoskeleton specifically adapted to help the elderly move, reach, and grasp. This is not an easy task as special consideration is needed to make the material light-weight, and delicate. In the future, these suits may even feel more like soft smart pants, than rigid bodies made of bolts and metal.

AXO-SUIT Project

Getting things done

Care-o-bot 4

The next step is to allow these robots to help around the home. This will require them to have grippers so they can fetch medicine, or a bottle of water. The robots may be remote operated, or may follow your commands in an autonomous manner. This has been the focus of the team behind the Care-o-bot robot. Their robot for assistive living, now in its fourth version, is the result of years of development and more than six related European projects.

The team behind the Care-o-bot also worked with CASERO, a robot that can help workers in care homes take over the heavy lifting. The robot can be used to collect the laundry, or carry water bottles around.

CASERO has certainly been a great help for us in our day to day work, transporting things [. . .]. It saves us time, and we can spend more time with the residents. – Silke Mlakar – care home worker

And if you believe the Robot-Era project, you might even send your robot out to shop for groceries, or pick up a prescription at the pharmacy.

Keeping you company
However sophisticated the robot, you may find yourself emotionally attached to its daily presence and enjoying its companionship. Human-robot interactions with the elderly need to be carefully assessed to make sure they are providing just the right level of interaction to be as helpful as possible, without being misleading. One of the most successful companion robots to date has been Paro the robot seal developed by AIST in Japan. The robot pet reacts to touch and has been shown to calm dementia patients and improve social interactions. This new form of Robot Therapy has also been shown to have benefits beyond eldercare, including to improve social interactions in children with autism.

https://www.youtube.com/watch?v=uFMenahpJtI

Making your home smart
And why not make your home a robot? A connected home could automatically check that the cooker is off, order food when the fridge is empty, remind you of appointments, and handle the entertainment system. The home may also coordinate a suite of mobile robots, including your vacuum cleaner, or other task-specific helpers. These smart living spaces, which build on the latest trends in Internet of Things, machine learning, and robotics, could deliver on the promise of better care outcomes.

Like many robotics technologies, integration is key. To move things along, universities are building dedicating assistive living spaces that will allow them to explore integrated homes in a well controlled research environment.

Barriers and prospects
Technology for assistive living leads to real challenges with privacy, ethics, and liability. The act of caring comes with deep responsibility, and potential for harm if not done carefully. In fact, most carebots developed in the laboratory have not made their way to the home. Public acceptance is still quite low, with the latest Eurobaromoter survey on autonomous systems reporting that 51% of European respondents are uncomfortable with having a robot to provide services and companionship to elderly or infirm people. Much of this is due to a lack of exposure to the technology, which will improve as robots become more prominent in the care sector. Thanks to the International Standards Organisation (ISO), there are also new standards for carebots, which should help pave the way for startups and SMEs who would like to enter the sector. The EU market for robots and devices assisting elderly people is estimated to reach €13 billion by 2016. Given this potential, Europe has been heavily investing in assistive living within the Horizon2020 robotics programmes, and also through the European Innovation Partnership on Active and Healthy Ageing, the Active Assisted Living Joint Programme, and national programmes such as the UKs Long Term Care Revolution project.

This is needed as we are still very far from the robot in the movie Frank and Me. Making robots is hard, and we’re just starting to see robots for assistive living leave the laboratory to help with specific tasks such as walking or eating. More versatile carebots still require some work, and most important, plenty of real-word experiments. Fortunately, any developments in assistive living have the potential to improve quality of life for the elderly and carers. And it will become a necessity in the future.

Read the previous article in the series here.

The ten-part series on European Robotics will be published every two weeks on the SPARC website and Robohub. Funding for the series was provided by RockEU – a Coordination and Support Action funded under FP7 by the European Commission, Grant Agreement Number 611247.

UPDATE: Only 7 days left to back Sweep! They are now almost 80% funded.

Sweep is a small, lightweight and low-cost laser scanner. It spins a laser range finder to form a 360 degree view of the world, up to 10 times per second. What makes Sweep different is who it’s designed for. Until now, sensors like Sweep were too expensive to be used in cost sensitive products, relegating them to research, industrial, or military applications. With Sweep, we aim to bring the awesome accomplishments of the last two decades of LiDAR research out of the lab and into consumer products!

Sweep is the culmination of years of development work, and like so many inventions, it came as a bi-product of wanting to make something else. We started off developing outdoor consumer robots for the home. We wanted to make a smart product that could navigate through typical yard environments, avoiding obstacles and keeping track of its charging station location. We didn’t like the hassle of other solutions, like buried guide wires, and knew a better way would be to have the robot form a map of the environment. We quickly realized to do any kind of mapping we would need a scanning LiDAR (or something similar) that works outdoors. It was then we discovered that there were no affordable LiDAR sensors on the market that met the requirements.

So, we set out to make one ourselves!

We designed Sweep to be very small and light! It fits right in the palm of your hand and weighs a tad less than most smart phones today. Sweep is also really quiet, something you may have never thought about until you’ve used one that makes annoying sounds as it spins. You won’t be hearing this scanner.

After more than a dozen iterations, we arrived at our current production ready design. We’ve discovered that the key innovation with Sweep will be its ability to perform much of the required data filtering internally. Most LiDAR sensors output a tremendous amount of data, which is great for applications where power and cost are not an issue, but cumbersome for consumer applications. For example, aerial vehicles may only want to know where the closest obstacles are. Sweep is equipped with several sensing modes designed to make interfacing with lower power controllers possible.

Testing with beta units has been successful!

For more than a month we’ve had beta units in the hands of testers. We’ve received great feedback on how people want to use Sweep.

Companies like Dispatch Robotics want a sensor to help guide their delivery robot through city streets. Others want to use it to navigate through grocery isles and office spaces. They are all excited about how Sweep can cut down the parts cost of their products by thousands of dollars.

 At Dispatch, we are very excited by Sweep. LiDAR is a very powerful sensing modality and low-cost LiDAR will have significant impact as we develop and grow our autonomous vehicle fleet.”

Uriah Baalke, Dispatch Robotics

The Sweep is a great fit for high school robotics. It is easy to setup and use, robust, and is at an incredible price point. Students can quickly explore mapping and navigation problems with little prior experience. Best yet, the Sweep is virtually student-proof – it can survive a high school lab environment.”

Charles Williams Mentor, Cupertino High School Robotics

How does Sweep compare to other sensors used for obstacle avoidance?

Traditionally low cost robotic vehicles have used sonar, structured light cameras, or stereo vision to sense their environment, but they all have a limited range. When following user controls or GPS directions they may only have milliseconds to react when obstacles come into their field of view. In contrast, Sweep has a range of 40 meters, giving much more time to react to approaching obstacles. It also works in all lighting conditions, making it more reliable in the real world.

We’re targeting the initial release of Sweep toward early adopters and developers looking to try out the technology. As we receive more insight from our customers about their specific applications, we will refine future versions of Sweep to meet the demand. Likely areas of improvement include additional internal data filtering modes, more compact packaging, faster update rates, longer ranging capability and more environmental hardening.

The ultimate goal of Sweep is to empower new and existing applications with a smart and affordable scanning LiDAR solution!

Contact

More information can be found at their website: www.scanse.io

Thier kickstarter can be found here: https://www.kickstarter.com/projects/scanse/sweep-scanning-lidar

You can contact them directly at: Team@scanse.io

Source: Wonder Workshop/YouTube

Spoiler alert. It’s April 1. But this is actually happening, just not quite the way SF educational robot startup Wonder Workshop describe it in this wonderful video about their new release – WonderPaw. Wonder Workshop launched their first robots Dot and Dash with a very successful Kickstarter in 2013.

San Diego based cognitive science startup CleverPet have released a ‘games console for pets’. CleverPet won the 2015 Robot Launch startup competition and was in the first Qualcomm Robotics Accelerator program. They are already teaching dogs (and cats) to be gamers. I think coding is getting closer.

https://www.youtube.com/watch?v=fMQ6WuTcsLE

iRobot Braava jet 240. Source: irobot.com

iRobot has been streamlining its operations to focus on consumer products and enhancing shareholder value. Recent moves to divest their defense division, launch a low-cost Braava Jet floor cleaner, and investing in 6 River Systems all attest to their strategy.

Divested defense division

In a February transaction valued at $45 million, iRobot sold its Defense and Security division to Arlington Capital Partners. The divestiture ends iRobot’s dual focus on the military and consumer markets and ends a multi-year revenue slide in the defense division. The sale was a strategically planned transition as the Iraq and Afghanistan wars wound down.

Colin Angle, iRobot Chairman and CEO, said: “In the spring of 2014, we engaged Blackstone Advisory Partners LP, now known as PJT Partners, to review strategic alternatives for our Defense and Security business. After a thorough and deliberate process, we’ve concluded the sale of the business to Arlington Capital Partners will maximize shareholder value by allowing us to focus on our much larger Home segment.”

Launched new low-priced floor cleaner

Earlier this month iRobot launched the Braava Jet Mopping Robot to add to their wet floor care business and to generate a new revenue stream beyond the Roomba line of vacuum products. The new robot is small — about 6″ square and 3″ high — with a nifty carrying handle — and focused on cleaning hardwood floors and tight spaces by dry mopping, damp mopping (uses 60% of water compared to wet mode), and wet mopping. Each mode has a unique pad easily snapped onto the bottom of the robot (and snapped off over the trash bin) and identified by the robot as to which of the three functions it is to perform. The new little robot’s best feature, however, is its low price: $199.

The Braava Jet is to be marketed heavily in China where the more expensive previous version of the Braava floor cleaner did quite well in year-over-year sales. In fact, according to CEO Colin Angle in an analysts financial call, said that growth in China was more than 70% year over year in 2015, driven primarily by the successful adoption of previous Braava models given predominately hard floor surfaces in the region. Hence the new lower-priced device is expected to be ideal in both the China and American markets.

Increasing shareholder value

In a recent letter to shareholders iRobot described its shift in focus toward the high-growth home robot business and by investing in projects that show the greatest promise for outsized returns.

iRobot is doing that with its existing and new products but also through its venture arm, iRobot Ventures, which just invested in 6 River Systems, a Boston-based startup of ex-Kiva executives developing fulfillment automation for e-commerce and retail operations. iRobot Ventures previously invested in Petnet, a smart feeder for cats and dogs, and Paracosm, a 3D vision and mapping technology company.

As an aside, Red Mountain Capital Partners, a VC which owns 6.1% of iRobot shares, and that invests in undervalued small cap companies and attempts to enhance and realize shareholder value through active ownership, is attempting to add two board members to the iRobot board at the upcoming stockholders meeting.

“Throughout our nearly year-long engagement with iRobot, it has become clear that the Board will only take action in reaction to significant shareholder pressure. As such, we have nominated individuals who are highly qualified and would bring a much needed shareholder voice to the boardroom. Red Mountain has consistently called for improved Board oversight with respect to the Company’s allocation of capital, cost management, return on invested capital and corporate governance policies,” said Willem Mesdag, Managing Partner of Red Mountain.

In the letter to shareholders, iRobot does not recommend these two board members but another two of it’s picking while citing that iRobot has delivered total shareholder return of 66% over the past three years compared to 59% for peers and 50% for S&P 500 companies.

A modular telepresence system. Source: wikipedia

In our final post for this series, we’ll talk about the future of telepresence.  For most robots telepresence is just the beginning, a means to an end. Many of the robots in this series are meant for office, medical, or home. But it should not be forgotten this same technology can easily be implemented for dull, dirty, and dangerous work, typical of robots. Allowing human operators to teach robots through telepresence creates a synergy along with higher levels of autonomy.

New robots help navigate the world

Take Henry Evans with Robots for Humanity. In 2002, an unfortunate brain stem stroke left Henry a quadraplegic. Telepresence provided the abilities to help him live his life. Whether using a Beam for a TED talk (see below), a Parrot drone to fly around his garden at home, or a PR2 to fold laundry, Henry has been able to take back control of his life through robotics with a condition that would have otherwise left him bedridden.

Consider your audience, and whether that’s intended

Knowing the operator of the robot is one thing. When Willow Garage launched the Heaphy Project back in 2012, they failed to consider who was on the other side operating the robot handling dish washing duties, which turned out to be rather creepy for the crew. While the concept of using a human anywhere in the world to control a PR2 was technologically advanced, there was the human element (even ones used to working with robots), that needed to be considered. The PR2 robot outsourced their dish washing duties to the world via Amazon’s Mechanical Turk. And though it had promise, it only lasted a month.

Human-like telecommunication

If anonymously operated robots are unnerving, maybe Nayang Technical University’s EDGAR is more comforting. Operators can project their face onto EDGAR’s, instead of a flat monitor, mimicking the gestures of the operator. It is fully controlled by a Microsoft Kinect. The university also developed ‘Nadine’ a social robot that operates like Siri or Cortana. Implementing the technology of EDGAR and Nadine would allow you to nearly duplicate yourself, at least from the waist up.

Better vision display

One obstacle in telepresence systems is lack of peripheral vision. But companies are working to solve this issue. Other technologies being developed include DORA, created by a team of students at the University of Pennsylvania.  By using the Oculus Rift all the head movements of the operator are mimicked by DORA. DORA solves the lack of peripheral vision issue by giving users the ability to look around, giving them a better sense of the environment. It’s the difference between watching something on TV versus actually being there. While this may not necessarily be important at weekly staff meetings, that increased visual awareness in an emergency response situation is vital.

Rise of the personal assistant

Designing Jibo.

And finally there is the rise of the personal assistant. While there are home service robots like Buddy, don’t disregard products like Jibo or Amazon’s Alexa.  While Jibo and Alexa are stationary right now, my hunch is that they won’t be for long.  I would also be on the lookout for an entrant from Google, Apple, or Microsoft to make their way into this scene, by means other than a smartphone.

While we are still a long way from seeing ‘Rosie’ enter our homes as a fully capable service robot, telepresence will lead the way for most.  The technology has come a long way since Pebbles was first introduced, but we’re about to see an even bigger change in the coming years.

Forbes has once again expanded their “30 under 30” list this year to celebrate the achievements of the up and coming; the main list now covers 20 different sectors, and an inaugural European edition has also been released, with 10 sectors. While the expansion of the list dilutes the brand (it’s more like “900 under 30”), it does highlight some interesting trends in robotics, AI and automation. Advanced manufacturing, conversational systems and human-augmented AI are key themes on this year’s list. And you’ll recognize some of these bright young minds from their contributions on Robohub.

Advanced manufacturing, 3D printing and rapid prototyping

Tim Sandy and Markus Giftthaler were honoured on Forbes “30 under 30” list for their work on the In Situ Fabricator mobile construction robot.

• Karishma Shah – Google[x] Rapid Evaluation Program Manager
  Google Alphabet’s youngest hire, Shah cofounded a natural language processing project at Google[x], led operations for the Project Wing drone delivery service, and now is program manager for Google’s rapid prototyping team.
• Markus Giftthaler and Timothy Sandy, PhD candidates at ETH Zurich’s Digital Fabrication lab
  Giffthaler and Sandy are developing techniques and tools for robotically fabricating complex structures on building construction sites as part of the Swiss National Centre of Competence (NCCR) in Digital Fabrication. You may have read about their work with architect Kathrin Dörfler on the In-situ Fabricator at Robohub.
• Danny Cabrera and Ricky Solorzano, Cofounders BioBots
  This company makes 3D printers and inks that can print living tissues.
• Phil DeSimone, Cofounder Carbon3D
  Carbon3D builds 3D printers for manufacturers that use a chemical process so that printing can be achieved 25 to 100 times faster than traditional 3D printing methods.
• Ionut Budisteanu, Founder VisionBot
  VisionBot has developed an affordable pick-and-place machine for automatically assembling integrated circuits; the machine is aimed at makers, hobbyist and SMEs looking to turn their prototypes into products.
• Max Friefeld, Cofounder Voodoo Manufacturing
  Voodoo Manufacturing offers scalable 3D printing services for single part prototyping up to high volume production.
• Maxim Lobovsky, Cofounder Formlabs
  Formlabs makes desktop 3D printers.

Drones

Philipp Oettershagen was honoured by Forbes 30 under 30 for breaking the solar powered UAV flight endurance record – 81 continuous hours of autonomous flight!

• Philipp Oettershagen, PhD Candidate ETH Zurich AtlantikSolar Project
  Oettershagen has been busy breaking solar powered UAV flight endurance records with the Atlantik Solar Project, which you may recall seeing on Robohub.
• Tom Brady and Danny Ellis, Cofounders SkySpecs
  SkySpecs makes software for inspection drones, allowing end users to automate inspection and analyze inspection data.
• Yash Mulgaonkar, PhD Candidate at U Penn
  Mulgaonkar’s research is focused on developing rapid fabrication methods for drones and other robots, and on training robots to coordinate together on tasks.
• Alec Momont, Founder Drones For Good
  Drones for Good leverages open source drone technology to explore how drones can be used for social good, such as delivering emergency supplies and medication.
• Sampriti Bhattacharyya, Founder Hydroswarm
  You may recall hearing from Bhattacharyya on Robohub — she’s made our Women in Robotics list in 2014, and also did an ICRACam pitch at IROS earlier that year. Her company, Hydroswarm, makes autonomous underwater drones for swarming applications.

Health and medicine

Luna is a rehabilitation robot for orthopedic and neurological patients by EGZOTech.

• Harbaljit Sohal, Postdoc at MIT
  Sohal develops neural implants that can be more easily integrated by the human body.
• John Barrett, PhD at Newcastle University
  Barret’s research focuses on neuroprosthetics and brain-machine interfaces
• Michal Mikulski, Founder EGZOTech
  EGZOTech is developing physical therapy robotics for automated diagnostics and treatment of neurological disorders.
• Patrick Slade, Cofounder PSYONIC
  PSYONIC develops low cost artificial hands
• Dhananha Jayalath and Chris Wiebe, Cofounders Athos
  Athos develops smart clothes that use sensors to help athletes understand which muscles they are engaging.
• Ben Harvatine, Founder Jolt
  Jolt develops sensors for detecting sports concussions.

Conversational robots for customer service

A Skolkovo startup, Promobot makes retail robots with conversational capabilities.

• Dmitry Aksenov and Mikhail Naumov, Cofounders DigitalGenius
  DigitalGenius provides natural language processing to provide big companies with conversational software robots for customer service that can answer questions in real time.
• Oleg Kivokurstev, Cofounder Promobot
  Russia’s answer to retail robotics, Promobot is designed to answer customer queries, distinguish between repeat customers and new ones, and learn people’s shopping preferences.
• Andrew Flachner, CEO and Cofounder RealScout
  RealScout is a service for realtors and their customers that uses machine learning to respond to natural language queries, to help home buyers to personalize their search criteria and find features that may not be included in a standard MLS listing.
• Matthew Ramirez, Cofounder WriteLab
  Writelab uses algorithms to provide immediate feedback to students about the grammar, spelling and structure of their writing assignments.

Human assisted AI for augmenting and automating bespoke products and services

• Navid Hadzaad – Go Bulter
  The concierge app GoButler launched in 2015 uses “human assisted AI’ to fulfill requests such as dinner or flight reservations via text messaging.
• Marcela Sapone – Co-founder Hello Alfred
  Hello Alfred is another concierge service that combines ‘intuitive technology with human intuition’ to anticipate your needs. The service offers home cleaning, dry cleaning, errand delivery, grocery shopping and other services.
• Maran Nelson, CEO and Cofounder Clara Labs
  Another example of “human assisted AI”, Clara Labs offers virtual administrative assistant services to executives and enterprises. NLP and AI are used to automate and streamline, while professional human assistants handle complex requests and do quality control.
• Kieran O’Neill – CEO and Co-founder of Thread
  Thread combines the savvy of human stylists with algorithms that track your style preferences and can quickly search through millions of products to hone in on items that meet your personal taste.
• Levi Young and Dana Zingher, Cofounders Enclothed
  Enclothed efficiently pairs personal stylists and customers by using algorithms to build a profile of your style preferences, size and budget, and searches for products to deliver to your door.
• Miles Penn and Rafi Witten, Cofounders MTailor
  MTailor is an app that uses the camera on your smartphone to measure your size and use the data to create custom-fitted clothing. YCombinator startup
• Caroline Walerud, Cofounder Volumental
  Volumental uses 3D scanning technology to find (or create) the perfect fitting pair of shoes, and they are looking to adapt the technology to eyewear next.
• Ben Alun-Jones, Kirsty Emery and Hal Watts, Cofounders Unmade
  Unmade offers custom machine-made knitwear; users pick and upload designs, sizes, yarn-type and colours, and Unmade uses a combination of knitting machines and knitware experts to finish your garment for you.

Smart homes and connected devices

• Will McLeod, Cofounder Keen Home
  Keen home makes smart vents to help you control the temperature of your home, room by room. McLeod is also cofounder of SmarterShade, a company that manufactures smart windows that respond to light and temperature by changing their tint.
• Michael Wang, Cofounder FutureAir
  FutureAir makes connected fans and air conditioners for efficiently managing indoor air quality.
• Kristjan Maruste, Founder CoModule
  CoModule offers a hardware/software package that bring connectivity to electric bikes and scooters, providing theft protection for users and vehicle diagnostics to manufacturers to help them improve their products.

Machine learning and algorithms 

• Scott Clark, Cofounder and CEO SigOpt
  SigOpt uses algorithms to optimize A/B testing for websites and applications.
• Nicole Hu and Ahmad Wani, Cofounders One Concern
  One Concern uses machine learning and predictive analytics to asses damage after natural disasters in order to help emergency service workers.
• Alexander Lavin, Research Engineer at Numenta
  Lavin is working to develop artificial intelligence by reverse-engineering the human cortex.
• Rob Bishop, Founder Magic Pony
  Magic Pony develops machine learning approaches to video enhancement, prediction and compression.
• Lucy Stonehill, Founder BridgeU
  BridgeU uses algorithms to match prospective students to the universities that best match their interests and career choices.
• Steve Marsh, Founder Geospock
  Geospatial data in real time for autonomous vehicles and other applications.

Courtesy of Fellow Robots, Inc.

In our previous post we looked at socially engaging robots and how they are helping to break down barriers to remote presence. Another area on the fringe of telepresence is service robots. These robots operate autonomously, but have the ability to be controlled in telepresence mode when the need arises. The symbiosis between robot and machine allows these robots to take care of easier things, while allowing humans to take over when it needs help. As autonomy improves, the bar moves higher and higher.

In October 2014, Suitable Technologies opened the first retail store staffed only by Beam telepresence robots. Two months later, Orchard Hardware in mid-town San Jose began using the semi-autonomous OSHBot by Fellow Robotics. OSHBot has image and voice recognition enabling it to guide customers up and down aisles to the items they are looking for — most of the time. Fellow Robotics, still in the pilot phase for the project, is improving certain processes like natural language recognition. Phrases like, ‘lawn mower’, ‘lawnmower’ or ‘lawn-mower’ can be a problem. However if an issue does arise, an associate from another store can login to help with more technical questions. No different than doctors using telepresence robots in rural hospitals when an expert isn’t physically available.

Silicon Valley isn’t the only place where you can find examples of service robots in retail.  REEM, by Pal Robotics, recently spent the summer on Yas Island in Abu Dhabi.  When at the mall she (yes, she) helped shoppers and tourists find their way, along with taking lots of photos. The team at Pal Robotics are also working on a bipedal unit called REEM-C, a robot that could potentially rival Honda’s ASIMO. REEM has two advantages: its use of ROS and availability to researchers. As of now, ASIMO uses proprietary software and he’s not available for sale.

Service robots are also entering homes as well. Korea’s Future Robot first unveiled FURo-i at CES in 2015, a home assistant robot, designed to maintain your home while away and chat with friends and family when you are there. Robot Base, out of NYC, also debuted ‘Personal Robot’ at CES in 2015. Think of Personal Robot like Siri on wheels, which can play your favorite music and remind you of upcoming appointments, ‘Personal Robot’ comes with advanced connectivity and autonomous algorithms to automate your home, like turning off lights and turning down the thermostat when you aren’t there. Recent media attention has gone to Buddy, by Blue Frog Robotics, due to its highly successful Indiegogo campaign (perhaps you saw it on RoboHub). Buddy is certainly the cutest robot of them all. Buddy can integrate with IBM’s Watson cloud services improving natural language and object recognition, along with the typical personal and home assistant functionality you would expect.

We’re now reaching the end of our telepresence series. In the final part, we’ll talk about the future of telepresence and where it could be headed.

Intel CEO Brian Krzanich during his keynote at CES 2016. Source: Consumer Technology Association

Intel’s Brian Krzanich described the use of embedded chips and cloud services to enable experience-based transactions. While many of these services are about driving sales, others are about enhancing user experience. Krzanich provided many examples, but four stood out as he made his case:

1. In a new Guinness World Record for the most unmanned aerial vehicles airborne simultaneously, 100 flying drones flew and shone their colored lights in sync with an orchestra playing Beethoven’s Fifth Symphony. Because it was so colorful, and timed to the music, Krzanich characterized the event as a potentially safer and reusable replacement for fireworks shows.https://youtu.be/mOBQXuu_5Zw
2. Using augmented reality, the ModiFace mirror enables consumers to try out different makeup looks (blush, eye shadow, lip stick color, foundation, glosses, etc.) and then buy their favorite color and product combinations. Typically done in public in department stores, sampling makeup can be an embarrassing process for some. An augmented reality product such as this one disrupts the process and provides a better customer experience.
   
3. Krzanich also demonstrated a Yuneec Typhoon H with an onboard RealSense 3D camera and chip, enabling a follow-me collision-avoiding drone that will be available later this year as a consumer product.
4. A pair of Oakley sunglasses provided the sensors and communication to track, interact, coach and provide data extrapolated from sensors tracking the wearer’s progress, comparing that progress to set goals, and providing spoken coaching and responsive reports along the way – the result being an experience instead of a pair of sunglasses.

(As an aside, Intel recently announced its acquisition of Ascending Technologies, the German developer of the collision avoidant autopilot system used in the video above. Last year Intel also made a big investment in Yuneec (whose drones now include onboard Intel RealSense cameras and chips) and Airware (a competing autopilot developer). And this week Intel invested in robotics startup Savioke, maker of the Relay robot, which autonomously navigates around hotels delivering toothpaste, towels, Starbucks coffee and other items.)

IBM CEO Ginni Rometty onstage at CES 2016. Source: Consumer Technology Association

IBM CEO Ginni Rometty told a packed CES audience that Watson and IBM were changing the nature of data processing from transactional to cognitive. Last year Robert High (CTO of IBM’s Watson Group) said that the emerging era of embodied cognitive computing is leading to “cognition as a service” — for example, a welcome 3rd hand for a lab technician, or a concierge or office assistant such as Jibo or Echo, or an assistant in field settings like search and rescue. The cognition process involves machines interacting with humans in a variety of ways, including via text, verbally, with tactile and visual cues, and with gestures. Cognitive algorithms and cloud computing are the keys to Watson’s feats, and they also happen to be where Rometty has pushed IBM since her tenure began.

Rometty described Watson’s progress thus far and demonstrated on stage many areas where applying Watson to an application is changing the nature of the experience. It’s not enough to just be able to hear what a user says. Watson must be able to understand what they want, be able to make that happen, and then interact back with the user in as conversational a tone as possible. SoftBank’s Pepper robot is an example of how this works. In this excerpt from Rometty’s presentation, she and SoftBank Robotics’ Kenichi Yoshida announced that IBM will provide global distribution and support for SoftBank’s Watson-powered Pepper robot as they scale up to begin selling into China and the US. Pepper has already sold 7,000 units in Japan and is in 300 bank branches, and 100 stores.

Bottom line

These two CES keynote presentations illustrate how artificial intelligence and data synthesis will provide the backbone to enable meaningful and productive interaction between humans and machines — not only on screens, but with gestures, visual cues and spoken understandable communication to and from smart devices and robots of all types. And it’s not just a near-term future they foretell — they give examples of where it is happening already.

Robots on the show floor of CES Unveiled Las Vegas on January 4, 2016. Source: Consumer Technology Association

CES is truly a global technology event: 3,800 exhibitors (of which 500 were startups); 2.47 million sq feet of exhibit space; 170,000 industry professionals (of which 50,000 were from more than 160 countries, including a Cuban delegation)!

Massive, exhausting, noisy, crowded, colorful, fun

The key words one heard from passers-by and sales people were: smart; connected; robotic; autonomous; self-driving; drones; IoT (Internet of Things); healthcare; fitness; apps; sensors; cameras; China; Taiwan; AI; headsets; virtual reality; augmented reality; and Mercedes Benz’s concept car.

Exhibitors attempted to show products that corresponded to those buzzwords, and visitors were “bombarded with early versions of tomorrow’s tech that are bound to feel janky and incomplete,” said Farhad Manjoo in the NY Times.

Smart shower heads that reduce water flow when you step away to lather up; smart fridge cameras that send a view of what’s inside  your fridge to your smartphone while you’re shopping at the store, or to a flat panel screen on the outside door of the fridge; big TVs (some up to 170″/432cm) with curved screens; virtual reality headsets; panelled lighting arrays; follow-me drones and carriers of all types; ski airbags (similar to boating life vests); Parrot’s new single wing drone (similar to senseFly’s eBee); the new Star Wars BB-8 toy from Sphero; wristband follow-me wearables; every type of workout wearable and sensor; avatars with customized faces (can be your face); pet games and food dispensers; makeup mirrors that overlay on your face different makeup combinations; bi-color LED lights for indoor ag farms; huge walls of TV screens showing every type of spectacular scene; face-tracking cameras; and connected cars and their driving, navigation and entertainment systems.

The show was organized by areas with sections for 3D Printing, Apps, Augmented Reality, Cyber & Personal Security, eCommerce, Education & Technology, Family & Technology, Fitness & Technology, Gaming & Virtual Reality, HDMI, Health & Wellness, iProducts, Kids & Technology, Robotics, Smart Home, Smart Watches, Sports Tech, Unmanned Systems, Vehicle Intelligence, and Wearables — essentially the whole gamut of electronic consumer products. Fitness, sports tech, vehicles and their systems, all had particularly mammoth areas.

The biggest exhibit spaces included two Chinese companies: Hisense and TCL. Other super-large exhibition spaces were for Samsung (the absolute biggest), LG, Nikon, Canon, Panasonic, Sony, Mercedes, Intel and Qualcomm.

• Hisense is a Chinese multinational white goods and electronics manufacturer headquartered in Qingdao, Shandong. It is a state-owned enterprise with publicly traded subsidiaries.
• TCL Corporation is a Chinese multinational electronics company headquartered in Huizhou, Guangdong.

The most notable companies NOT exhibiting were Apple, Facebook, Amazon, Google and IBM — although most had hospitality suites and/or meeting rooms for their ad teams to meet with clients who produced consumer electronic products, and IBM’s CEO was one of the keynote presenters (see below).

Business getting done

In a NY Times article, the serious side of the CES spectacle was highlighted:

“A lot of business gets done at CES, often away from the show floor, in the labyrinthine warrens of meeting rooms across the Las Vegas Strip.”

Very true. Even companies that didn’t exhibit (like Twitter and IBM) had quiet spaces to demonstrate products, talk pricing and agreements, and generally have time and space for one-on-ones with customers and prospects. Although IBM is no longer in the consumer products business, they had a large meeting room set aside for their customers who were. Twitter created a miniature city in two large ballrooms at one of the hotels. It had shops, restaurants, a bar, a theatre, and an outdoor park. Each was a meeting area for Twitter’s ad sales team to meet and greet customers.

Hourly press events hyped, but some made news

There were more than 25 press conferences held at the show. Many were announcing additional products to an existing product line. A few described new products. And some, like Toyota and Intel, provided pertinent information about profound changes about to happen.

Toyota held a press conference led by Gill Pratt of DARPA fame, who now is the CEO of Toyota Research Institute (TRI) wherein he announced their new research staff. One member of that staff was James Kuffner, the previous head of Google’s robotics group known as Replicant. His departure continues the robotics shakeup at Google. Details here.

Other press events ranged from entertaining to informative and included Yamaha Ventures announcing their cooperation with SRI International to jointly turn Yamaha’s MotoBot into a real thinking and navigating robot.

“This project will be able to push several boundaries: visualizing data about human motorcycle operation, further quantifying the relationship between rider input and machine behavior, and then using the resulting know-how to build even better vehicles,” explains Amish Parashar, Director of Strategic Business Development at Yamaha Motor Ventures and Laboratory Silicon Valley Inc.

Keynotes were particularly informative

Intel, IBM, Netflix, General Motors and Volkswagen all had keynote presentations, but seats for Intel’s were the most highly prized.

Intel’s CEO Brian Krzanich was the featured speaker and he covered so many topics one really has to watch the whole hour and forty minute presentation to capture the full impact of all that he described. The import of what he said — that we are moving from a time of transactional systems to one that is experiential — seems predictive of the next few years in electronics, the digital world, robotics and artificial intelligence. Watch the video above or read the condensed version here.

https://youtu.be/VEq-W-4iLYU

IBM’s CEO Ginni Rometty told a packed CES audience that Watson and IBM were changing the nature of data processing from transactional to cognitive and that this process would change computing and lead to providing cognition as a service. IBM describes the cognitive process as providing the 3rd hand for a lab technician, very similar to the experiential descriptor used by Intel’s CEO. During Rometty’s presentation she described how Watson is working with SoftBank to provide global distribution and support for their Pepper robots. Read the condensed version here.

A bit of cynicism: Lots of overzealous hype

Overzealous marketing can be seen regularly in crowdfunding campaigns. CES was similarly full of examples of ventures claiming to be able to provide something useful when, in fact, they need funding to see whether they can actually do what they are promising. Sometimes these companies hire social media people to help promote those very things using viral marketing in their arsenal of advertising tools. There are many examples — but the 2014 Robot Butler campaign is a paradigm classic.

A joint marketing campaign for Quirky (which was promoting their array of smart home sensors, switches and products) and subsidiary Wink (which makes a hub that combines them into a smart home) featured a catchy video ad suggesting that smart homes were better served by Wink products than by a robotic butler. The video, entitled Like a robot butler, but less awkward, showed a couple in bed being uncomfortable with their robot butler peeking in on them as if it were sentient. The ad was supported by the distribution of a bunch of cardboard shipping boxes for non-existent robot butlers that were dropped off on the streets of San Francisco waiting for trash pickup as if they were the empty boxes of real robot butlers. The promoters hyped sightings of those boxes with lots of blog posts, tweets and other social media, and even set up a Robot Butler website.

AdWeek finally exposed the situation:

“Well, it turns out this was just a social media sensation. There is no real Robot Butler, at least not this one, and the whole misleading campaign, was just for an app that controls home appliances.

“The company behind the app and marketing was called Wink which is owned by Quirky, a New York-based company that makes Internet-connected devices for the home and other gadgets, and General Electric is an investor in Quirky.

“Quirky is for real and subscribed to Wink’s parody marketing campaign based on the Robot Butler. The problem was there was no indication that the robot was a hoax, it was not selling out of stock as claimed, it would not be ready for shipment to consumers, and it was not being reviewed by reputable news sources.”

Quirky recently filed for bankruptcy; the Wink component is being sold off as IP to Flextronics International; the advertising “parody” (which, in this case, appeared to be a euphemism for “phony”) failed; and a real robot butler is still many years off.

Bottom line:

CES draws huge traffic to the worlds of digital, electronics, robotics, IoT and consumer products. Everyone wants to learn about products and thematic or even paradigm changes that will affect their lives in the near future, and over 6,000 members of the media from all over the world were there to gather that information. Their observations have been — and will be — top news stories for months to come.

There will be mistakes made in some of those reports as there was in a recent NPR story about Pepper costing $20k when actually it sells for $2k. Nevertheless, the CES experience is a valuable stimulant for all of us in the various industries that make up the robotics industry.

The two keynotes by the CEO’s of Intel and IBM shown above describe a trend from transactional to cognitive to experiential. This has import to the robot industry in a variety of ways.

• by IBM’s Watson being incorporated in SoftBank’s Pepper social robots
• by the ever-increasing value of the chips, cameras and systems being offered by Intel, Qualcomm and others
• and by the expectation of users to be able to communicate and be understood by their robotic assistants.

There’s no reason to overdo the promotion of future products by falsification, stealing content or otherwise hyping a product beyond it’s capabilities or possibilities. People read most of the stories and reports coming out of CES because they want facts about products they may want to buy. They want the truth — and they can handle the truth.

Photo courtesy of University of Freiburg and University of Bonn

How many of us have envisioned intelligent robots operating and assisting us in our homes with everyday tasks? Different users typically have varying preferences and expectations when it comes to tasks, such as tidying up or organizing objects in containers. For example, every person has their own way of organizing groceries or books on their shelves. Moreover, each environment is unique with respect to the items and number of containers that a robot could encounter. This makes it challenging for experts to pre-program robots with strategies for performing such tasks in order to cope with all potential situations and to accommodate different users.

To address this challenge, researchers from the University of Freiburg and University of Bonn have developed a technique to enable service robots to predict personalized preferences of their users. The work is based on collaborative filtering, a data mining paradigm widely used by recommender systems like Amazon or Netflix to make personalized recommendations. For example, an online store could use information about what an individual has purchased previously and predict what products they might buy in the future. Analogously, this work aims at predicting how users prefer to arrange objects (e.g., grocery items, toys, books, etc) in containers (e.g., shelves and drawers) by learning from different users over time. By observing how a user has already organized objects in the environment, the robot can predict the best way to organize new objects without needing to constantly query the user.

To train their system, the researchers gathered data from over 1,200 survey participants using crowdsourcing. Each participant answered questions about their preference for grouping different object classes (e.g. sugar and pepper) together in the same container. Using such data, the approach discovers latent patterns in user preferences with respect to grouping pairs of objects. Accordingly, the robot can then predict the best way to organize objects for a new user based on partial knowledge of his or her preferences. When sorting the objects, the technique also takes into account the available number of containers in the environment. The video below explains the main idea behind the work and illustrates the method using a PR2 robot.

Moreover, the approach is able to utilize information mined from the Web to assist the robot in case it encounters objects it has not learned about yet. The idea is to leverage semantic hierarchies of objects that are mined from online stores, from which the robot can compute similarities between objects. By combining data from multiple online sources into a mixture of experts, the robot can for example learn to group cake mix with flour since they both tend to be found under the “baking” section of online stores. This is done in a way that complements the collaborative filtering method above by considering the preferences of the specific user in question.

Finally, the nature of this collaborative filtering approach allows robots to improve their predictions by learning from users over time. With more data in the system (e.g., perceiving a variety of scenes), robots will get better at learning models of tidying up by discovering patterns shared between users. This will provide future robots with the flexibility to tailor tasks to the unique environments they are in. This concept is illustrated in the video below, which shows how the arrangements predicted by the robot change according to the scene it perceives:

Relevant papers

Nichola Abdo, Cyrill Stachniss, Luciano Spinello, Wolfram Burgard
Collaborative Filtering for Predicting User Preferences for Organizing Objects

Nichola Abdo, Cyrill Stachniss, Luciano Spinello, Wolfram Burgard
Robot, Organize my Shelves! Tidying up Objects by Predicting User Preferences
IEEE International Conference on Robotics and Automation (ICRA), Seattle, USA, 2015

In an article about the pace of sales for the SoftBank Pepper robot, the China Post reported that Taiwan-based Hon Hai Precision (AKA Foxconn) has sent a team of 30 to survey the US market for future acquisitions of robot production firms.

On December 27th in Japan, another 1,000 of the $1,600 Pepper robots were sold online in just one minute  — this makes 7,000 sales in the past 7 months. The next sale date is January 28th. Foxconn is currently producing 10 Pepper robots per hour at factories in Yantai (Shandong Province, China) and is working to improve efficiency and raise production to 15 per hour.

The Pepper app store for add-on applications offers a range of more than 200 free and paid apps. These apps range from quiz games, English picture books, hairstyle and clothing chat games, timers, dance instruction, lie detection, brain games, exercise trainers, animal sounds, food apps like beef bowl and noodle shop locators, piano playing, baseball talking, English for kids and many more.

Pepper, created initially by France-based Aldebaran to act as a “social companion for humans,” is advertised by SoftBank as not only being able to read human emotions, but also to respond to emotional cues such as laughing or frowning.

Softbank recently upgraded Pepper to be able to memorize and store data on human responses by using cloud-based artificial intelligence applications developed by the company’s subsidiary, Cocoro SB.

The newsworthy part of The China Post story was Hon Hai Precision’s 30-person US delegation to explore purchasing companies that can help Foxconn increase its production of this very complex robot. Once sales expand from Japan to China (and then the rest of the world), production will need to keep pace; hence the concern and exploratory shopping trip. The joint venture between Alibaba, Foxconn and SoftBank has provided hundreds of millions of dollars for production ramp-up costs, which are likely to include money for capital expenditures such as robots and other automation devices, as well as for acquisitions of companies that make those devices.

If you liked this article, you may also be interested in:

• Foxconn and Alibaba invest in SoftBank Robotics as Pepper goes on sale in Japan
• 2016 will be a pivotal year for social robots
• Nestlé 1st big buyer of Softbank’s Pepper robot
• SoftBank invests in Fetch Robotics
• Japanese telcos vie for share in consumer robot-as-a-service business

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Jibo got $16 million from Asian VCs to enable Jibo to speak and sell in Japan and China, while Blue River Technology got $17 million from a group of agricultural VCs to expand product development to new areas, as funding for robotic ventures continues to soar. UPDATED To include funding for Soft Robotics, Inc. Flyability, and Naïo Technologies.

Jibo, the Cambridge-based maker of a family robot that expects to deliver 7,500 pre-ordered units and then launch a marketing campaign in March/April of 2016, got $16 million in funding from two Asian VC firms. The funding is to localize apps and gestures and enable Jibo to speak Japanese and Chinese so that it can be sold to those markets.

“We’ve received significant interest from Asia. I just got back from Japan and there’s a different kind of interest in that market for robots. In the US, it’s more about what can this robot do for me. But in Japan, there’s almost a folk lore to robots,” said Jibo CEO Steve Chambers.

Aaron Tilley on the Forbes staff wrote: “Jibo has a robot head that swivels on a static base in a cartoon-like manner. Users can talk to Jibo, and it will talk back. Jibo can also take pictures or play games. The robot’s camera recognizes users and remembers their preferences. The company is integrating Jibo with a bunch of third-party services to open up what the robot can do. A Skype integration, for instance, would allow the user to take calls on the robot and then have the robot’s camera follow them as they move around. Some companies are interested in integrating Jibo with other smart home devices. The company is also now working on these third-party integrations with Internet services in China and Japan.

Blue River Technology, a Silicon Valley startup, has perfected its lettuce-thinning technology and is now providing that service to 10% of the growers in the industry. This new round of funding is to expand their technologies to be able to sense each individual plant, determine its health and needs and then precisely apply the correct amount of care, plant by plant, at tractor speed, the very definition of precision agriculture.

Blue River uses computer vision and robotics for various agricultural tasks. It was founded in 2011 by two Stanford University alumni, and has made breakthrough algorithms and robotic solutions for identifying weeds and selectively killing unwanted plants. Its solution is particularly suited to organic agriculture and for fields with chemical-resistant weeds.

Osaro, a San Francisco startup, received $3.3 million in seed funding to accelerate the development of AI for robots to speed up the training and programming process.

Soft Robotics Inc., a Boston startup, received $3 million in Series A funding from Material Impact Fund, Taylor Farms Ventures and Haiyin Capital. The funds will be used to enable rapid growth and widespread deployment of their unique gripper system for advanced manufacturing and food handling and the ag industry not only in the U.S. but in China as well.

Naïo Technologies, a French startup with its first sales in 2015, raised $3.3 million from the Emertec and CapAgro investment funds, a WiSeed crowdfunding campaign and via its previous shareholders. The newly obtained funds will allow the company to finance international expansion, R&D activities and to double sales in 2016.

Kurion, a California integrator of service robots for high-risk applications, acquired Oxford Technologies, a 60-employee UK and EU provider of robotic services for nuclear facilities and clean rooms, for an undisclosed amount.

Flyability, a Swiss drone startup, raised $2.53 million. “This round brings Flyability the resources needed to launch its first product to market, which will be available in 2016”, said Patrick Thévoz, co-founder and CEO of the company. The company has already shipped prototypes to its first customers focusing on industrial inspection in the energy and transport infrastructure industries, and first responders such as firefighters, police forces, and search & rescue professionals.

BOTTOM LINE: Money continues to flow to robotic ventures well into the holiday season. Over $1.2 billion has been invested in more than 50 robotic startup companies, and an amount well above that figure has been involved in 29 acquisitions. All this in one year.

These new robots — and the proliferation of mobile robot butlers, guides and kiosks — promise to recognize your voice and face, and help you plan your calendar, provide reminders, take pictures of special moments, text, call and videoconference, order fast food, keep watch on your house or office, read recipes, play games, read emotions and interact accordingly. The list goes on.

These products are attempting to be analogous to a sharp administrative assistant who knows your schedule, contacts and interests, and engages with you about them to help you stay informed, connected and active.

According to a research study by Tractica, annual shipments of consumer robots (a category that includes robotic vacuums, lawn mowers and pool cleaners as well as social robots) will increase from 6.6 million units in 2015 to 31.2 million units worldwide by 2020, with a cumulative total of nearly 100 million consumer robots shipped during that period.

Although robot vacuums will remain the largest segment of the market over the next several years, the fastest growth will occur in robotic personal assistants — a category that is nascent today. According to the report, “the next 5 years will set the stage for how these robots could fundamentally transform our homes and daily lives.”

As social and companion products come to market, they incorporate artificial intelligence from the past several years. Yet almost every day there are breakthroughs in learning systems that will soon be commercialized and incorporated into future personal devices. These AI improvements will enable ubiquitous robotic and robot-like personal assistants and companions. Consequently, today’s social robots are transition devices for early adopters  to scrutinize, play with, suggest improvements to, and talk about — which is why 2016 is a pivotal year. It’s the time when companies will sell enough units to learn whether their bots provide a real and lasting service, or if they are just a passing fancy.

These new products fall into three categories, and the primary ones (as determined by launch date and invested capital) are shown below:

Mobile devices

• For homes
  • Pepper, by SoftBank Robotics. A mobile humanoid robot that sells for $1,600 plus an additional $200 per month for Internet service, updates and maintenance. Only speaks Japanese and French at present but Chinese and English are planned for early 2016. Peppers are selling at a steady rate of 1,000 per month.
  • Buddy, from Paris-based Blue Frog Robotics. A squat little $649 device that whisks around on wheels and casters and will do many of the things Jibo will do. Buddy will begin shipping and selling in 2016.
• ​For offices, stores, hotels, public spaces and museums
  • SaviOne/Relay by SaviOak. A hospitality robot that autonomously navigates hotel hallways and elevators to deliver items to hotel guests.
  • Store assistants and guides – multiple vendors are beginning to provide mobile kiosks that can identify items and navigate to where they are stored.
  • Public guides and assistants answering common questions – for airports, museums, galleries, public spaces, and soon, restaurants, by multiple international vendors.
  • Special-purpose mobile bots such as
    • Budgee, a tote-carrying follow-me device that communicates through your phone, by Five Elements Robotics.
    • CaddyTrek, a follow-me golf-bag carrying mobility device from FTR Systems.

Tabletop assistants

• Jibo, the spin-out from the MIT Media Lab headed by Cynthia Breazeal. Twists and tilts and communicates like or better than Siri, initially only in English. Jibo will sell for $749, and connects to your home WiFi network. This recipient of more than $60 million in crowdfunds and equity investments, with $16 million in new funding that will be used to localize Jibo with language and apps for the Chinese and Japanese markets.
• Sota, by Japan’s largest telecom company, NTT, will sell for about $800, plus a monthly service of around $30. In addition to its ability to verbally communicate with the user, the robot can also assist the user with health functions by interacting with wearable devices to check blood pressure and heart rate.

Non-robotic home assistance devices

• ECHO by Amazon is a stationary voice-activated hands-free device that provides information, answers questions, plays music, reads the news, checks sports scores or the weather, and more.
• Rokid, by Chinese home automation company Rokid, will soon be introducing a stationary device with intelligent robot capabilities like omni-directional voice recognition using eight microphones, face recognition, and an ability to integrate into smart home automation systems.
• MJI (More Joyful Innovation), a cute egg-shaped communication device with a 5″ screen, is being geared towards the elderly and those that required communication assistance. MJI can send and receive messages and phone calls without requiring any manual input using voice activation. MJI will begin production and sales early in 2016.

In addition to the products mentioned, there are many, many other cute bots designed for children, STEM education, schools, therapists, disability centers, and academia. They are all worthwhile products, but unlike those listed above, they are not being built for mass consumer adoption.

Bottom line

At this year’s iREX Robot Expo in Tokyo and at the Beijing World Robotics Conference (both held last month) social, humanoid and mobile robots were the biggest crowd pleasers. Ten years ago PopSci reporter Tim Hornyak wrote “Loving the Machine” — a book about Asia’s long-time fascination with robots. His insights still appear to be true: the Japanese really do have an unusual affinity for human-like robotic things. This is why so much money is flowing to help these new social robots quickly adapt to the Chinese and Japanese language markets, and to provide localized apps from their software stores.

If you like this post, you may also be interested in:

• Case study shows new roles for robots in today’s economy
• IFR predicts double digit growth for service robots through 2018
• Japanese telcos vie for share in consumer robot-as-a-service business
• The second wave of social robots is here
• Natural language: The de-facto interface convention for social robotics

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Tabletop telepresence devices began to pop up on the market about two years ago. Though its a small slice of the telepresence market, it’s differentiated enough from other categories to be mentioned in a separate post. Many telepresence users simply want the ability to pan and tilt around a room. While this solution doesn’t work well for places like museums, it’s perfect for classrooms, meetings, or get togethers where you don’t need much mobility.

The scene pictured above is taken from a hybrid course taught at Michigan State, where both online and local students can participate in a traditional classroom setting. By comparison, classes that are taught completely online are limited to group video chat. The hybrid class concept was tested with both tabletop telepresence, like the Kubi, as well as with full size devices like the Double. With the telepresence robots, students were no longer viewing the class from a wall mounted monitor, and they reported feeling more engaged in the class and participated more actively than previously. The research is ongoing but the tabletops seem to have received a better initial response. You can learn more about Michigan State’s research on integrating telepresence into classrooms in the following video:

So far there are three entrants in this category: Kubi by Revolve Robotics,  Pivot by WowWee, and the TableTop TeleMe from MantaRobot. All work with iOS and Android, while Kubi seems to be the only one that works with Windows.

Kubi is finding niches in ambulances for telemedicine, where mobility is restricted and a smaller footprint has an advantage. Another advantage of these tabletop models is power: since you’re not mobile, you can be plugged in continuously and not worry about needing downtime for recharging.

As with the full size tablet robots, you are still limited to the embedded camera on the tablet of your choosing. This is one area where I’d like to see some development to obtain more peripheral vision.

With products like Jibo and Amazon’s Echo showing up in our homes, I anticipate tabletop devices will become more prevalent. A stationary hands-free device that can pivot while you move around saves you from having to robot-proof your home; fixing door thresholds and moving stray cords can be a cumbersome chore at best, or a complete floor plan change of your home at worst.

Next up are telepresence toys, where we will scale down to fun size using a smart phone.

Double makes an entrance on hit TV series Modern Family.

Personal telepresence robots have exploded onto the market thanks to the help of tablets, smartphones, and crowdfunding sites. Geared toward the economics of personal use, these robots typically cost less than $3000 (tablet typically not included) and don’t require a monthly subscription. While the telemedicine category of telepresence devices has been plagued by lawsuits, the only drama in this category is the love (or hate) of your smart device.

Padbot

Working with an iPad or iPhone (iOS), you have three choices: the Double, the TeleMe or the Padbot. The Double, is only available with iOS and has received the most exposure, appearing in both the Modern Family and Community television series. The Padbot, which launched via Indiegogo, was designed and developed by InBot out of China. While it initially went for as low as $299 during the launch campaign, it can now be had for $799 in the US. The TeleMe and TeleMe2 from MantaRobot, have been out for a while and work with iOS and Android. They are also the only ones I’ve seen that really work with Windows-based devices like the Surface Pro.

Twinbot

Like the Double, but for Android, the TwinBot has a strikingly similar appearance. Though its Indiegogo campaign failed, Robotshop.com picked it up for sale. While it doesn’t have a telescoping neck, it does have the ability to tilt the tablet up and down. The “Telepresence RobotRig” by Endurance is based out of Russia, and while they are a relative newcomer to the scene, they seem pretty ambitious with their plans to introduce an autonomous mode.

The Origibot is currently the only telepresence robot with an arm and manipulator on the market. This was another Indiegogo campaign success (you might remember having seen the campaign on Robohub). The first backers will soon be getting their robots, so we’ll give it a few months for owners to tinker with the design. The lack of arms is seen as an issue, as it provides a tangible means for interaction.

If you don’t want to bother with purchasing a tablet, there is the Beam+ from Suitable Technologies. A slimmed down version of the Beam Pro, the screen is embedded into the device so you are platform agnostic.

Beam +

Oculus by Xaxxon was actually the first to hit Kickstarter back in late 2011. Using a netbook atop the Oculus base allowed you to roam around. They combined it with RoboRealm to allow for advanced mapping and computer vision. The beauty of using a netbook is that you can now integrate with ROS, creating a true robot according to a purist’s definition.

Up next, we’ll take a look at a niche category — tabletop telepresence — where the lack of mobility can often be an advantage.

Source: Bloomberg

On Singles Day 2015, a holiday for the Chinese singles and youth market, Ecovacs Robotics sold $47 million worth of robotic products. Ecovacs only has three robotic products: a line of vacuum cleaners, a window cleaner, and a security and air purification device.

Ecovacs Robotic’s Deebot robotic vacuum cleaners sell for between $180 and $500 in China; their robotic window cleaner sells for $350; and their Famibot mobile wifi and air purification robot is only available for pre-order. Dividing $47 million by $250 (which presumes that most of the Singles Day sales were vacuums) equals 188,000 robotic units sold on a single day! Much of those sales were sold online on Alibaba. Ecovacs is taking orders for their Famibot, the security, wifi and air purification mobile bot with no specific delivery date mentioned. Deebots and Winbots are available for immediate delivery online with Amazon and Ecovacs Robotics.

The phenomenon of Singles Day was originally created by some college students in China as a special holiday to celebrate people who were not in a relationship – people who were essentially single. November 11, or 11/11, was chosen for the annual holiday, because no other date on the calendar has as many 1’s, or “singles”. Alibaba has trademarked the Chinese double 11 symbol in their effort to make Singles’ Day (11/11, November 11th) an international online shopping event. From Ecovacs point of view, they’ve certainly succeeded!

Alibaba Group Holding Ltd. ​reported $14.3 billion in sales during China’s Singles’ Day. The results, posted by the Chinese e-commerce giant in the early morning hours on Thursday local time, were 54% higher than last year’s Singles’ Day and were better than many analysts had expected.

If you liked this article, you may also be interested in:

• Dyson robotic vacuums go on sale in Japan
• Residential robotic vacuum cleaner market poised for stellar growth
•  Why is Japan the first to get Dyson’s new 360 Eye?

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Launched last week on Indiegogo, the Nailbot prints instant custom art onto your fingernails from your phone. Behind the concept is a new kind of company — a movement to inspire confidence in girls and women, and to provide them with the opportunity to engage with technology that is relevant to their lifestyle. Preemadonna teaches them how to start a business, how to build prototypes of their ideas, and how to code.

A main outreach avenue for Preemadonna is our Ambassador program. Perks include VIP access to exclusive Nailbot & Preemadonna events where we test upcoming prototypes of our product. Girls joining the program are also taught to create art using various computer programs. This is then uploaded to our app and printed using a Nailbot. Ambassadors also have first access to our Maker Kit, which teaches them how to build their own touchscreen printer.

More than just a company with a product, Preemadonna is devoted to being socially conscious: we work with a variety of community partners to empower girls and young women to believe in themselves and follow their dreams. We want every girl to embrace her dynamic nature and realise that having multiple skills and interests is not a problem. Each girl should know that she can be a Preemadonna: a smart and beautiful girl.

One of our first partners was Alexa Cafe, a week-long summer camp for girls focused on teaching them about technology and leadership. We gave presentations to introduce the girls to the Nailbot and explain the prototyping process. It was easy to tell that Alexa had opened the girls’ minds because the questions they asked were insightful and detailed. It’s an inspiring place to visit. We also recently visited MakerGirl, a program for young girls run by students at the University of Illinois. Our presentation there focused on the prototyping process and how we use 3D printing, and the girls had a chance to use our latest prototype.

Preemadonna Ambassadors, January 2015.

We’ve found that we are able to produce a more desirable and engaging product by working directly with our customers. Specifically, our prototypes have evolved with customer feedback from our pre-teen and teen supporters. Some voiced the need to have diverse galleries of art that can be modified and consumed easily, with applications beyond fingernail printing. Girls want stickers and temporary tattoos from Preemadonna! Others wanted more diversity in color choice; teal, mint and rainbow were very popular. Many loved the ingenuity in our first Nailbot prototype — which is a clever swipe-to-print concept that is not motorized — but they voiced concern that the early prototype would not reach the level of accuracy they wanted (you can check out our Nailbot Journey in our Indiegogo campaign).

Fundamentally, these girls helped validate our concepts and business model. The digital art marketplace is one of the Nailbot’s biggest draws, and the ability to contribute back to the community and having access to Preemadonna founders is what will keep them engaged.

Join us on our journey and involve the creative and dynamic girls in your life!

Casey Schulz and Pree Walia, co- founders of Preemadonna.

The latest batch of 1,000 Japanese-speaking Pepper robots sold out in one minute after they were made available online by Japanese telecom company SoftBank. This brings the total Pepper robots sold thus far to at least 7,000. A new batch of 1,000 will go on sale 28 November.

This will be the 6th batch of Pepper bots to go on sale since the launch in June, 2015. Priced at $1,636 for the robot plus $200 per month for the online service and maintenance contract, and only available in Japan at the present time, there are about 200 apps available for the device. These apps range from quiz games, English picture books, hairstyle and clothing chat games, timers, dance instruction, lie detection, brain games, exercise trainers, animal sounds, food apps like beef bowl and noodle shop locators, piano playing, baseball talking, English for kids and many more.

Foxconn is a partner with Alibaba and SoftBank, in a new venture called SoftBank Robotics. Foxconn is also the manufacturer. Foxconn started to produce Pepper robots in February, churning out five per hour. Currently, the hourly production has risen to 10 units and they are planning to further boost production to 15 units per hour by raising the number of workers on the production lines to 1,000 from the current 700 and employing automation in the production process. Depending on how many hours they work, they could be producing up to 2,000 Peppers a week at that rate.

SoftBank hasn’t announced when they plan to release Chinese- or English-speaking Pepper bots except to say sometime in 2016.

Could robot chefs really have arrived? Moley’s approach, the robotic kitchen, is basically a flexible workcell, and in manufacturing that’s nothing new. But providing the essential ingredients – feeding the robot chef – needs further consideration.

Is 2015 the pivotal year for robot chefs, the year when it’s started to look realistically possible? When Moley announced its robotic kitchen back in April, the media jumped on the story as a promising glimpse into the future. Could robot chefs really have arrived? As robotics’ professionals, we’re understandably skeptical about such news stories – since the 1960s we’ve heard that robot servants are coming. But if Moley manages to overcome one major issue, their approach could have real potential. Why? Because their kitchen is basically a flexible robotic workcell, and in manufacturing that’s nothing new.

When you tell people that you work in robotics, one of the most popular responses is: “So, when are you going to make a robot that cooks and does the washing up for me?”

Robot cooks and maids have been promised to us since personal robotics were first predicted in the 1960s: In 1966, Shakey was introduced as “the first electronic person”, in the 1980s Omnibot could carry a tray of drinks and in 2009, several “Robot Chefs” were center-stage at Japan’s Food Machinery and Technology Expo, flipping pancakes and arranging plastic sushi.

Finally, this year in April a London company called Moley robotics gave the first live demo of their motion-capture based robotic kitchen.

Could robotic chefs really have arrived?

Why robot cooks are so challenging

The traditional challenges for creating a cooking robot have been the challenges of operating within a human environment, including navigating in cluttered environments, operating safely around humans and animals, as well as classifying unknown objects.

We are probably still a long way off from producing safe, multi-purpose robotic servants which can operate reliably within a cluttered human environment.

Moley has removed many of these challenges by changing the requirements of a robotic cook.

Their approach seems to be: Why make things difficult by trying to design a robot which can work in any kitchen?

Instead, they have chosen to supply the whole robotic kitchen. Safety is provided by a protective window, in the same way that we ensure safety for industrial robots.

The Moley robotic kitchen is more like a flexible manufacturing workcell than a “robot servant”. Instead of manufacturing mechanical parts, it flexibly manufactures food. The biggest difference is that it is programmed by a motion-capture of a real chef preparing the dish, and is designed to copy the organic motions of the chef as closely as possible.

This approach to programming could be a source of complications. However, it is far less problematic than the question of how to reliably chop and prepare the ingredients before cooking.

Moley would do well to learn some lessons from the existing cooking robots that are already used in the world today. Though several robots exist, none of them have reliably solved the Feeder Problem (i.e. providing the essential ingredients for your robotic cell).

Food manufacturing: robots already make your food

It should come as no surprise – we eat food prepared by robots all the time. There are many robots already used in the food manufacturing industry. Chances are you have probably eaten at least something recently that has been touched by a robot. For example, robots are often used to butcher meat.

But, using a robot to make a home-cooked meal is not the same as processing raw ingredients in a factory. Even so, people have been eating robot-cooked meals for several years.

It turns out that the Moley robot is just the latest in a whole line of robotic cooks, with well-established machines like the Thermomix being a starting point.

Although it doesn’t look much like a robot, a Thermomix is more than a robotic food processor. It follows simple programs, but lacks advanced sensors. It chops, cooks, steams and blends, allowing it to cook a lot of varied meals, making it as versatile as many of the existing cooking robots in China.

China: home of the robot chef

Right now, China seems to be the home of the robot chef. During the last five years, various restaurants have been using wok-tossing robots, which cook stir-fried food using pre-measured and pre-chopped ingredients. The same cooking design has even been turned into vending machines and robot restaurants.

Measuring and chopping are supposedly complex tasks and so are still carried out by humans.

These simple machines are really no more complicated than the Thermomix, and are far more involved than the very successful Ultraman noodle-shaving robot, which has basically removed a menial job from the hands of human chefs entirely. Its humanoid appearance is little more than a marketing gimmick.

Such robots demonstrate that profitable markets for highly specific cooking robots exist, if those robots are not overly complex.

The brand-new Sereneti kitchen robot, announced at the end of September, has taken the same approach. It basically consists of a pot-stirring robot. Feeder trays, very much like those of the wok-tossing robots, pour pre-measured and pre-chopped ingredients into the pot.

However, these are obviously far less complex than the robotic kitchen that Moley is proposing.

The Feeder Problem: the challenge for true robot chefs

Truly versatile robot chefs are a bit more complex than a wok-tosser, as is clear when you watch this demonstration of a Motoman dual-arm with Roboiq hands cooking an egg sandwich.

However, just as with the simpler systems, there is still no easy solution to the feeder problem.

Every ingredient must be measured out and placed in the right location for the cooking operation to be a success. This is the core challenge that Moley will have to deal with. It currently does not chop or prepare any of the ingredients (they are placed in position by human operators).

As the CRC Handbook of Mechanical Engineering says: “Experience so far has shown that in most instances, it is the feeder that fails in the workcell, not the robot. Feeding methods must be carefully considered when designing a workcell.”

Moley would do well to focus heavily on their feeder method. Perhaps it would make more sense to employ modified industrial food slicers instead of trying to keep every aspect of the operation anthropomorphic, as they are trying to do now. Or perhaps they’ll come up with an even more ingenious method.

The expected release date of the robot kitchen is 2017. So, we will have to wait until then to see if Moley manages to overcome the feeder problem. I look forward to seeing how they solve this core manufacturing challenge.

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See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

I’m pleased to announce today [Monday] the unveiling of a new self-driving vehicle company with which I am involved, not building self-driving cars, but instead small delivery robots which are going to change the face of retailing and last-mile delivery and logistics.

Starship Technologies comes out of Europe, created by two of the founders of Skype, Janus Friis and Ahti Heinla who is CEO. The mission is similar to the vision I laid out in 2007 for the Deliverbot — the self-driving box that can get you anything in 30 minutes for under a dollar.

Here you can find the press release, a simple video and a collection of press and other videos.

Starship is still in early stages, but will be conducting a pilot project next year in the UK, and another in the USA shortly thereafter. Customers will be able to place online orders and have a robot come to their home immediately or on their schedule.

Why is this possible well before full unmanned self-driving cars can go into public use? There are all sorts of reasons.

• The boxes are not in a super hurry
• They will go slowly and cautiously
• They don’t mind detours, and can take the safest rather than shortest route to you
• It’s not a big deal if they have to pause if they encounter children or anything confusing or risky, or need to wait for a remote operator to solve a problem
• They will travel on the sidewalks, rather than the roads (already legal in many places, but work is needed in others)
• They will be slow and light, so that if something goes seriously wrong and they hit you, they won’t injure you
• They won’t hit you though, because they can come to a full stop in under a foot
• You don’t need crumple zones, airbags or other passenger safety features for cargo, making them simple and inexpensive

How big is the last mile? It’s huge. It’s not just what today’s delivery companies do. Most deliveries are actually made by customers who run out to stores to get stuff. The Starship robot will bring you things in less time than a round-trip shopping trip would take, for less money, and with vastly less energy, pollution, traffic congestion and parking. It’s a win for the store, the customer and for society.

https://youtu.be/MEWfsVPqKi4

It’s a really big win for those with disabilities or difficulty moving. The elderly are going to be able to live in their own homes with greater independence, even if shopping has become such a chore they were contemplating a senior home.

The robots will eventually create an “internet of parcels” (I guess the term “internet of things” is already in use) where physical goods can move around cities with an ease surpassed only by data. Not only will you be able to buy anything, you’ll be able to rent things on short notice too, or borrow them from your neighbours. The sharing economy can be enabled and the meaning of ownership may change.

The convenience of robot delivery will surprise people. A common question I get asked is “What does the robot do if you’re not home when it delivers?” and my answer is, “why would you want the robot to deliver when you’re not home?” Regular delivery runs on the driver’s schedule, robotic delivery will run on yours. Robots don’t mind waiting either, so you could ask a shop to put five pairs of shoes into a robot, and at home you could try them on and put four pairs back in the robot and keep the ones you like.

I also expect interesting changes in prepared food. It will be possible to run a “restaurant” inexpensively in a private kitchen and get ingredients and deliver dishes quickly and cheaply with no wastage. A family might even order different dishes from different locations to create a meal.

Nothing is 100% good for everybody — there will be disruption in the retail industry, and retailers who exist primarily so you can go get things will have trouble competing if they don’t embrace this model, but other retailers who are suffering from competition from the online stores may find they can now dominate with fast service.

Of course, there might be competition in the air. Our students at Singularity University were among the first to work on drone delivery with the Matternet project which is beginning a trial delivering for the post office on the steep slopes of Switzerland. Both methods face legal challenges, and both have their advantages. Drones will be faster and can cover unusual terrain, while ground robots can carry more with less energy and have an easier time landing. :-) I suspect people will tolerate small robots on their sidewalks more than drones with heavy packages over their heads, but we’ll see.

Note that I’m a special advisor to Starship on both technology and business, but this post is written with my own voice, and doesn’t speak on behalf of the company.

This article originally appeared on robocars.com.

Robotics is truly an interdisciplinary research field. It draws lessons from other research fields, while also contributing new knowledge to those fields, some more than others. Without a long history of robotics research, we might not have many of the technologies prevalent in the world today.

Of course, it’s hard to say for sure which of the many associated technologies would still exist if robotics didn’t. Robotics “takes” more from some research fields than it “gives back”. Computer vision, for example, has been highly influenced by robotics research. However, as you can see if you look at the history of computer vision, it has largely developed on its own, in parallel to robotics, and would almost certainly exist without robotics.

However, other technologies available to the modern consumer are so strongly influenced by past robotics research that they wouldn’t exist in their current form without it.

1. Inverted Pendulums

Scene from Paul Blart: Mall Cop 2.

These days, it’s not uncommon to see everyone from tourists to security guards riding around on motorized inverted pendulums. Of course, since 2001, the inverted pendulum has been “re-branded” as the Segway, thanks to the battery powered vehicle of that name and its successors.

The theory is simple, the center-of-mass is held above a pivot point that is usually attached to motorized wheels. With Segways, this center of mass is provided by the weight of the human rider. As the system is inherently unstable, the control system for the wheels must compensate to keep the whole system upright. In this way the rider can drive the robot by simply leaning forward.

Cubli, from ETH Zurich.

Inverted pendulums have been a long-standing fixture in robotics and control theory. Since the 1960s, they have been used as a fundamental benchmark to test controller performance, as well as being used to teach control theory. Many different control methods can be used and tested, from simple PIDs to neural networks.

Even though the concept of the inverted pendulum has been around for a long time in robotics, it took until 2001 for anyone to realize its commercial possibilities. When they did, the results were staggering.

How many other, simple robotic concepts are just waiting to be turned into a successful commercial ideas?

2. LiDAR and 3D scanning

Google LIDAR map.

LiDAR (from the words “light” and “RADAR”) is the latest in the line of wave-based range sensors, which began with its predecessors: RADAR (Radio Detection and Ranging) and SONAR (Sound Navigation and Ranging).

It uses light beams — usually lasers — to create high-resolution 3D point maps. Sensors detect the distance of the target by bouncing the beam off the target and measuring how long the light takes to return to the sensor.

Although LiDAR has a long history of development apart from robotics, ranging back to the 1970s, the latest wave of LiDAR 3D scanners has been a game changer for robots. Low cost scanners, such as the Hokuyu Laser Range Finders, have finally given robots a way of reliably detecting their environment. They are now so ubiquitous that it’s rare to see a mobile robot that doesn’t have a laser scanner.

Researchers have started to address many of the challenges that are unique to robotics, such as how to quickly detect objects from point clouds or how to manipulate objects with robotic grippers. These challenges would not have been explored by the original researchers of LiDAR technology. Robots operating in real-time need to perform calculations as quickly as possible, which has pushed the technology further than it would have progressed without robotics.

This is a perfect example of robotic researchers contributing new knowledge to another research field by applying their technology to engineering problems. This knowledge then feeds back into commercial products.

3. Unmanned Aerial Vehicles (Drones)

Drones are another example of a long-standing robotic technology that has recently been commercialized and “re-branded”, this time by the media. Drones (aka, unmanned aerial vehicles or UAVs) are flying robots and incorporate most aspects of robotics, including control systems, sensing, computer vision and navigation. Hobbyist drones are usually quadcopters, while the military drones are more like unmanned airplanes.

Quadcopters, or quadrotors, were the subject of robotic research for quite a few years before their current surge of popularity. Although four-rotor aircraft have existed since as far back as 1907, the modern quadcopter has really taken off in the last decade as electronics have reduced in size and cost. Numerous research groups use them to develop advanced control, such as collaborative mapping and autonomous navigation.

The public has mixed feelings when it comes to drones. On the one hand, they are rightly worried about the use of unmanned aerial vehicles as weapons of war. On the other hand, the public use of hobby quadcopters has skyrocketed (if you’ll excuse the pun). For example, they have revolutionized low-budget filmmaking by allowing anyone to shoot impressive aerial shots.

Drone development, which has long beencarried out by robotic researchers in labs, is now moving quickly into the commercial arena. What area of robotics is next we wonder?

4. Simultaneous Localization and Mapping (SLAM)

Real-time appearance-based map, based on SLAM. Image courtesy: Matthieu Mathieu Labbé

As a research field, SLAM is what we’d call “mature”, meaning it has been going on for a long time (since 1986) and any new developments in the field are relatively advanced. In other words, it is a well proven research field. However, it’s only been recently that we’re starting to see SLAM really take hold in the commercial world. Though it is not exclusively a robotic research field, it has been highly influenced by robotics and is one of the core topics in mobile robotic research.

As it’s name suggests, the idea behind SLAM is to create a map of the robot’s environment while simultaneously calculating where within the environment the robot is located. The classic example that has moved into the consumer world is the robotic vacuum cleaner (like the Roomba), which creates a map of your house while also cleaning up and locating itself in the room.

With the rise of self-driving cars, warehouse robots and location-based mobile applications, SLAM is only going to become more pervasive in the modern world. Without it, robots would find it almost impossible to operate in a human environment.

What’s Next?

The only question now is which key technology will become the next rising star to grow out of robotic research. Just like these four technologies, it will undoubtedly be something that already has a lot of research work behind it and is well proven in real applications. However, hundreds of research fields interact with robotics, while the consumer world can be fickle and unpredictable.

So we will just have to wait and see.

Image: Dyson

After a six-month delay to hone the robot for Japanese homes, and a year after the original launch announcement, the Dyson 360 Eye robotic vacuum cleaner has finally gone on sale in stores all over Japan and in Dyson’s new flagship retail store in Tokyo.

A recent TechNavio analysis of the residential robotic vacuum cleaner market forecasts a CAGR of 6.43% over the period 2015-2019. Another research firm predicts a 15% growth rate over the same period. Robovacs (as robotic vacuum cleaners for carpets and floors are called) still form a small percentage of the global vacuum cleaner market (18% according to Colin Angle, CEO of iRobot, makers of the Roomba line of robotic vacuum cleaners), but their acceptance is clearly growing at a steady pace.

The Dyson 360 Eye system is novel in that it creates a panoramic 360º view of the room and then navigates by triangulating fixed visible points. The video below shows the navigational process:

Dyson plans to launch the 360 Eye robot vacuum in the US, China and Europe during 2016.

Today, vacuums represent just half of Dyson’s $2.1bn in sales. The company’s technology pipeline for the next few years includes hiring 3,000 new people, launching 100 new machines and  four brand new product categories — all by 2020.

Advanced robotics will change the world of engineering for good. At Dyson, we’ve been developing robot technology for over 15 years – 200 engineers, 420 patents and £28m has already gone into our first robot vacuum. But our Dyson 360 Eye robot is just the start. The team is advancing the systems that make our robots more intelligent – able to understand environments and navigate with complex sensors and algorithms. The future is robotic.

Robotics Trends compared the 360 Eye to iRobot’s Roomba 980 in a side by side chart that indicates very similar functionality and high selling price, (the Dyson product is $250 more than the Roomba). Dyson claims it’s vacuum generates the highest suction of any robot vacuum. Both have comparable software apps but iRobot claims that the Roomba’s low height enables cleaning in places where the Dyson can’t go. Also, the vision systems are different, particularly in respect of how they map the area, plan their work and localize where they are.

Only sales figures from the marketplace will tell the real story of how consumers perceive any differences.

Komissarova describes why the timing for starting Grishin Robotics was just right, and shares some of the initial feedback from different parts of the robotics community.

She also talks about differences between the companies that get funded and the ones that that don’t, what it takes to be a successful entrepreneur in robotics, and the areas within consumer robotics where we are likely to see strong development in the next few years.

You can support Robots in Depth on Patreon. Check out all the Robots in Depth videos here.

If you liked this article, you may also be interested in:

• Robots Podcast#116: Grishin Robotics
• Dmitry Grishin on evaluating robotic investment opportunities
• Grishin’s first investment: Double Robotics

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

News Brief:

According to Dyson:

Bosch has installed control electronics into some of its machines to wrongfully increase energy consumption when in use – to cheat the EU energy label … Their behaviour is akin to that seen in the Volkswagen scandal.

Bosch denies the allegations, stating that:

We do not understand these assertions by Dyson and we strenuously reject them. All Bosch & Siemens vacuum cleaners are measured in compliance with European energy regulations. Appliance performance at home is consistent with laboratory performance – and any suggestion to the contrary is grossly misleading.

Read more:

• James Dyson accuses Bosch of cheating ‘like Volkswagen’ | The Telegraph
• Dyson’s robot vacuum is finally here…in Japan…for $1,200 | Mashable
• Bosch sues Dyson for “completely unfounded accusations of cheating” | Ars Technica

You might also be interested in:

• Why is Japan the first to get Dyson’s new 360 Eye?

photo by Pete Souza, Chief Official White House Photographer via Instagram

Telepresence robots have been around since the early 2000s, with a research project called PEBBLES out of Ryerson University in Toronto. When I first started covering this area a little over three years ago, there were only a handful of products available. Since then, the market has exploded, with a slew of robots ranging from the table-top Kubi and the sleek Double to the highly advanced Ava 500. They’ve also been on the move, heading out of the office, attending conferences, and touring museums. In this series I’ll be updating you on telepresence as is stands today, the various market categories, and where the field is headed.

Roughly broken down by pricing levels, we’ll start with enterprise or business class telepresence, where you’ll find high end robots like iRobot’s Ava 500 or Suitable Technologies Beam Pro. These cost several thousand dollars to start and usually have a monthly fee.

Telemedicine robots deserve a category on their own; with requirements for HIPAA and FDA clearance, these aren’t cheap and are not something something the average person or business typically needs.

Then there are the home or personal robots, like the Double, Padbot, and Beam+. These typically have fewer options, but are certainly more affordable. Often, as in the case of the Double, you’ll need a tablet to act as the brain of the device.

Likewise is the toy category, which typically uses a smartphone as a brain. The Romo or Wheelphone are better suited to roam around on a table rather than down a hallway. And if you’re looking for even economy, Kubi and the TableTop TeleMe offer telepresence without mobility. They’ve taken away the wheels, but still offer an interactive experience that allows the user to pan and tilt their view around the room.

Then we have the unique and unusual robots that push the boundaries of telepresence, such as the Telenoid or Orihime, or that cater to niche markets, such as those specifically adapted for use by the physically disabled.

And finally, there are the service robots such as BUDDY, PAL, and OSHBot, which while not built specifically for telepresence, still offer this as a feature. For example, the OSHBot has a telepresence feature that allows a customer in need of help to contact an associate who may be in another store and remote him or her onto the OSHBot screen.

Over the course of the series, I’ll be tallying about 40 different kinds of telepresence robots, a few of which have already gone away or never made it out of the research lab. Keep an eye out over the coming weeks!

* Note: Before I delve too deeply, we have to deal with a very controversial topic: are telepresence robots really robots?  I will be hijacking the definition of robot from Wikipedia, which states that a robot is an electromechanical device that can be autonomous or semi-autonomous. A device like the Double uses an algorithm that allows it to balance itself on two wheels while in operation, while iRobot’s AVA navigates autonomously. Many telepresence devices have some sort of obstacle avoidance, making them at least semi-autonomous. I am arguing that one or more sensors providing feedback, such as obstacle avoidance, is sufficient for referring to the device as a robot.

The service robotics industry is relatively new, diverse and picking up steam daily. Service robotics covers every activity except those described as industrial. These are robots that perform useful tasks for humans and are categorized as either personal or professional.

Service robots cross definitional borders. They collaborate safely with humans and they move goods of all types for all kinds of purposes. Mobile robots fly, swim, run, jump, clean and glide. They milk. They help. They assist in factories, shops, homes and hospitals. One significant difference between industrial and service robots is that, for the latter, there is no multiplier for additional costs associated with getting the robot up and operating in a safe fixed location. Service robots, particularly service robots for personal and private use, tend to be self-contained and/or plug and play and not in need of integration services, as is the case with industrial robots.

The International Federation of Robotics (IFR) have just published their World Robotics Service Robots statistical review of 2014 (with projections through to 2018). The 226-page $675 report details the sales revenue and units sold by category from a database of approximately 300 service robot manufacturers around the globe.

Revenue from the sale of industrial robots was $10.7bin, with an additional $21.3bn in spending for supporting services such as integration, peripherals, software and systems engineering — so $32bn in total. Service robotics (both professional and private) totaled $5.97bn. Therefore, the combined value of the robotics industry – service, support and industrial – for 2014 was $38bn.

• In 2014, professional service robotics rose by 11.5% from 2013. 24,207 units were sold at a value of $3.77bn. The IFR is projecting a growth rate of 19% in units and 11% in dollars through to 2018, 36,750 units and $5.7bn projected for 2018 (respectively).
  • Defense applications represent 45% of those figures (unmanned aerial vehicles followed by bomb fighting and de-mining robots).
  • Milking robots represented 24%, leaving 31% for medical and logistical robots.
• In 2014 personal service robotics rose 28% over 2013, with a value of $2.2 bn for 4.7 million units. The IFR is forecasting a growth rate of 27% in units and 35% in dollars through to 2018, with 12.25 million units and $7.3bn projected for 2018.
  • Household items (floor and window cleaners and lawn mowers) with higher price points account for the higher revenue increase over the percentage for units sold.

There are many, many variables that could seriously alter these projections. The IFR acknowledges this problem as follows:

The 4 year projections are conservative due to the character of the company feed-back. Typically companies only report projections of sales of existing products (or at least pre-series products that are about to be launched). Therefore a future product, Jibo for example, is not reported and counted.

Nevertheless, the projections are very likely to be seriously understated for a variety of possible reasons. For example:

• The acceptance and sale of hundreds of thousands of Pepper robots,
• An increased rate of adoption of home floor cleaning robots in the Asian marketplace similar to the success of iRobot in the English-speaking world,
• The acceptance and sale of millions of Jibo and other table-top robotic assistance devices,
• A near-term solution which enables collision avoidance, thereby letting mass quantities of drones and drone deliveries into the national air space,
• The collaborative robot marketplace could take off at an even greater rate than the present 70% year-over-year sales increase, as new low-cost robots are quickly trained and put to work for SMEs around the globe.

[The IFR produced their report and based their projections on a limited database of 300 service robot companies of which 15% were startups. The Robot Report’s database contains over 900 service robot companies and an additional 400 startups. The IFR’s distribution is: 23% from Asia, 36% from the US and Canada, and 41% from the UK, EU and elsewhere. The Robot Report’s database is quite similarly distributed for service companies. It significantly varies in where the startups are located: only 12% in Asia,  48% in the US and Canada, and 40% in the UK, EU, Israel and elsewhere.]

Using a BeamPro, Brianna Lempesis waits in line to buy an iPhone6s from the Apple Store in downtown Palo Alto. Photo: Suitable Technologies.

Robots are great for doing dull, dirty, and dangerous jobs, and few jobs are more dangerous and downright dull (at times) than waiting in line to buy the latest tech gadget. Last week in Palo Alto, California, and in Sydney, Australia, telepresence devices stood in for their human counterparts to buy the iPhone 6S. 

Both transactions took place without the humans ever getting in line. Brianna Lempesis, who works for Suitable, hopped in line in Palo Alto the morning the iPhone went on sale there. Lucy Kelly, who works at a marketing firm in Sydney and normally uses a Double for work, was able to hop in line the day before. Kelly on her Double in Sydney and Lempesis on her Beam Pro in Palo Alto were both able to operate their telepresence devices and complete the entire transaction in the comfort of their homes, while multiplexing themselves at their respective offices.

“This the most fun I’ve ever had waiting in a line,” said Lempesis. Though each event was seen as a publicity stunt, I expect this to happen more often as busy people with the financial means wake up to the idea that they can physically be in more than one place at a time.

I’m currently hatching a plan to use this idea for Star Wars: Episode VII The Force Awakens tickets, though I think Sphero’s BB8 might be more appropriate.

In the coming weeks, I’ll be covering  the current state of telepresence to give you an idea of just how prevalent it is, and why this isn’t going away. Watch for more soon.

Fully designed and assembled in China, Dobot, a new desktop, 4-axis, stepper motor, high precision robotic arm has launched its first Kickstarter campaign.

https://youtu.be/UcknDFiCxG4

Feature highlights:

●  High mechanical accuracy (0.02mm)
●  High repeat precision (0.2mm), 50 times better than uArm
●  Stepper motor equipped with high accuracy reducer
●  High strength aluminium alloy surface and processed by anodic oxidation treatment
●  Mechanical structure assembled by the state of art CNC cutting technology, ensuring its superb agility, stability and durability
●  Seven control methods including PC, mobile app, voice, vision, leap motion, geature and EEG (mind control, see demo: https://www.youtube.com/watch?v=RxU7ZhStuPA)
●  Easy click-and-drag control interface for beginners and also programmable for advanced makers, using Processing, Arduino, and C/C++ as primary languages
●  Affordable price starting from $399, making it affordable for both makers and the general public, Dobot’s design is a good fit for desktop applications.

Tech specifications:

●  Number of Axes: 4
●  Weight: 3kg
●  Payload: 500g
●  Range: 270 degree rotation
●  Position repeatability: 0.2mm
●  Material: aluminium alloy 6061
●  Controller: Arduino Mega2560
●  Communication: UART/Bluetooth
●  Power Supply: 12V 5A DC

The team has premiered its prototype at the 2015 Shenzhen Maker Faire, where it received positive feedback from makers, robot experts and open hardware communities.

“The motion is really precise, it’s not just a toy, it can also be used to build stuff,” says the CEO of Arduino, Massimo Banzi.

Dobot was founded in June 2014 by a group of industrial robot engineers based in Shenzhen, China. All the founders acquired extensive industry experience in robotics before joining the team. They have a firm belief that industrial precision robots should be on everyone’s desktop.

Virtual assistants are setting the bar for the kind of user experience people will expect from the social robots of tomorrow.

At the Apple party earlier this month, at the Bill Graham Civic Auditorium in San Francisco, CEO Tim Cook and other key execs took to the stage to announce their next-generation product offerings. Apple’s been setting trends in user interface (UI) and technical design for over two decades now and its latest products didn’t disappoint: Siri already inhabits our iPhones and responds to voice commands, but now she will soon be embedded in Apple’s TV remotes too, so that users can change channels, find weather forecasts and get sports scores simply asking for them.

Siri demonstrates just how far we’ve come from the early days of interfacing with computers, databases and other information systems. Whereas systems used to be able only to respond to constrained queries, such as a Google search, Siri is now intelligent enough to respond appropriately to fairly detailed, human-like, requests, such as “Show me the Modern Family episode with Edward Norton” or “Skip ahead seven minutes.” She can even respond to questions such as: “What did he say?” Siri will simply skip back 15 seconds to the previous line the actor said. It’s an innovative new interface for controlling TV and a host of other media, and it’s likely to change how we interface with computing even more significantly than the introduction of the GUI (which, if we remember, Apple also had a hand in rolling out).

In addition to Siri, there’s a swarm of other software robots descending from the clouds: Google’s Google Now, Microsoft’s Cortana, Nuance’s Nina, and the Amazon Echo, which plays music, reads books and can buy stuff listed on their site. All of them keep track of what you like, when, and are able to draw massive amounts of data from both your voice (gender, age, region and other vectors) as well as the words you use. Baidu announced Duer in the first week of September with the intention of providing a voice interface for the home and internet of things (IoT) services and healthcare support. The company also  plans to integrate it into self-driving cars.

And recently Facebook’s M was touted as a concierge service available through its messaging app. This is a smart play, as Facebook is manning the assistant with a crowd of  employees (called M trainers) to simultaneously answer requests and train the system to improve responses. It seems a short step for Facebook to place ads in M (much as they do in site content today), but the real revenue stream will be in collecting user data. For the time being, as with Baidu’s Duer, Facebook’s M is not voice-driven, but uses text as a feature within the Messenger app.

Our mobile devices are becoming natural language interface hubs for life management and, as a result, having a gravitational pull on an increasingly complex buzz of connected services and APIs.

There are many others: Samsung’s S Voice, LG’s VoiceMate, BlackBerry’s Assistant, Sirius, HTC’s Hidi, Silvia and Braina, to name a few.

We can also foretell the future by looking at less advanced natural language systems. Bots – essentially natural language oriented scripts – are a good indicator of where the robotics industry is at because bots are pervasive, useful, and simple to author. TwitterBots and FacebookBots crawl through these systems like bees in a hive, industriously providing retweets, reposts, summaries, aggregations, starting fights and flocking to followers. They can be bought, auctioned, sold, and deleted; you can buy 30,000 Twitter followers on eBay for as little as for $20, provided they’re all bots.

Several years ago Facebook estimated that around five percent of all accounts are bogus – this would put the number of Facebook fakes at around 50 million – while other, now-antique estimates range as high as 27 percent (that’s about 200 million trash-trawling bots). They’re relevant because emergent technology arrives from the fringe.

According to Gartner’s 2015 Hype Cycle chart, Intelligent Virtual Assistants still have a ways to go before they get good enough to go mainstream (likely, 5-10 years). But also according Gartner, roughly 38% of American consumers have recently used virtual assistant services. They predict that, by the end of 2016, around two-thirds of consumers will be using them daily. Other sources forecast that the global Virtual Assistant market will grow at a CAGR of 39.3% between 2015-2018, and the total market is projected to climb to more than $2.1bn by 2019. These numbers cluster around the trends in natural language interfaces.

These trends show no sign of altering their flight path. Our mobile devices are becoming natural language interface hubs for life management and, as a result, having a gravitational pull on an increasingly complex buzz of connected services and APIs. This means that things like search will change: we will no longer have to speak Googlese; paper and page metaphors will be supplanted by the more dynamic (and cognitively more addictive) character metaphor. And if trends in virtual assistants and intelligent helpers – software robots – continue, then knowledge-bases (such as Wolfram Alpha or IBM Watson) will continue to come peppered with a patina of natural language, allowing us to move through data faster, with less training, and in a more human manner.

This is the trend in software robots, and it is headed towards hardware, too.

Hardware is the new software

Software robots show us what hardware robots will be expected to do in the near future. First, natural language is the de-facto interface for a range of functions from social robotics to customer service and personal healthcare companions – not only because it increases the quantity of data collected, but also because it decreases the cost of collecting it. Not only because it replaces people, but because it amplifies them.

That said, the natural language interface, or voice UI, is only one of many that robots will be expected to provide. Virtual assistants can now perform a range of functions based on the online services that are commonly integrated. Since these services can now be integrated into any connected system, we can put together a laundry list of what hardware robots will be expected to do:

• Understand voice input (respond to commands, answer questions, etc.)
• Offer personal assistance (schedule appointments, set reminders, check stocks, etc.)
• Provide mobility assistance (give directions, predict traffic, find parking, etc.)
• Interface with connected devices (TVs, garage doors, lights, surveillance cameras, etc.)
• Allow you to buy stuff (and keep track of what you’ve already bought)
• Interface with social media (send photos, read tweets, etc.)
• Detect mood (read emotions, body language, save state, etc.)
• Build predictive models (track user behavior, save user state, etc.)

Robotics will increasingly adopt a voice UI, akin to what we see in today’s personal assistants, because task completion is simpler, faster, and more effective, menus go away and personality (the UX of NLP) is a lot of fun. These software robots are testbeds and proving grounds for what users expect from tomorrow’s hardware robots; they set a bar for user experience. Personal assistants, like their distant cousins from a hardware lineage, will soon be smart enough to reply to other robots that call us on the phone, and we will want to equip our Jibo, Nest or Alitalia system with it’s own resident assistant that will answer the phone when the robot from the cable company calls.

Whether you happen to be Siri or the gal working for customer service at the cable company, your job, your life, your car and your family is being invaded by the swarms of personal assistants changing tomorrow’s robotics industry today. We have a choice: either we design hardware robots as assistants and companions (to help us accomplish tasks and keep us company), or we design them like bots (to mull the garbage, aggregate the trash, and harass one another).

The future, it seems, contains both.

Transcript included.

In this episode, Audrow Nash speaks with Sergei Lupashin about Perspective Robotics’ tethered flying camera, the Fotokite Phi, which is currently crowdfunding on Indiegogo. The Phi is a portable light weight GoPro-carrying quadrocopter that flies without a vision system or GPS, and instead uses the tension on the retractable tether to determine where it is in space. According to Lupashin, the tethered leash provides a natural, easy-to-learn and accountable interface for controlling the Phi.

https://www.youtube.com/watch?v=aglTWdI-4Bo

Sergei Lupashin

Sergei Lupashin is the founder of Perspective Robotics, the Swiss company behind the Fotokite. Previous to that he worked in aerospace and participated in robotics competitions such as the DARPA Grand+Urban Challenges (autonomous cars). He was chief architect for the ETH Flying Machine Arena, where he enjoyed torturing little quadrocopters until they learned to do flips. He holds a BS in Elec & Comp Engineering from Cornell, an MSc + PhD in Mechanical Engineering from ETH Zurich (topic: aerial robotics) and is a TED Fellow. Sergei is passionate about building devices that are usable and useful in the real world.

Links:

• Download mp3 (14.3 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Link to Fotokite Phi Indiegogo campaign

Transcript

Audrow Nash: Hi welcome to the Robots Podcast. Can you introduce yourself to our listeners?

Sergei Lupashin: I’m the founder of Perspective Robotics, a company based in Zurich, Switzerland that is behind the Fotokite, the Fotokite Pro and the Fotokite Phi.

Audrow Nash: Fotokite Phi is currently crowdfunding on Indiegogo. Can you tell me a bit about the campaign and its goal?

Sergei Lupashin: This is our first attempt at building a product for consumers. We started off by building the Fotokite Pro, which is a specialized, more expensive product designed to be used for broadcast. With the Fotokite Phi we have tried to make something much more accessible both in terms of price and usability. It’s extremely portable and it can be used in lots of different situations.

We are trying to raise a minimum of US $300,000 … It’s a hardware product, so you have to build critical mass to make it accessible for a wider audience. It’s a very exciting step for us.

Audrow Nash: Can you describe the Phi?

Sergei Lupashin: I’m holding one in my hands right now … It’s a small quadrocopter that holds a GoPro, and it weighs only 12 ounces – about the weight of a small can of soda.

What’s unique about it is that you control it via tether. You hold onto what is essentially a glorified dog leash with some electronics, and you launch the Phi just by turning it on, giving the quadrocopter a twist, and letting it fly.

Audrow Nash: This doesn’t have the same sensors as most drones. Of course it has an IMU, but you’ve removed GPS, correct?

It’s a different experience from traditional drones because the interface is so physical: you feel pretty much the smallest motions of the Fotokite in the air through the string.

Sergei Lupashin: Exactly. One of the things we use the tether for is to figure out where the Phi is relative to the user. A normal drone does that by having a GPS receiver or having some sort of machine vision to figure out where it is. In our case, we use a tether that is kept under tension at all times. By calculating where that tension force points, the Fotokite actually knows where it is relative to you.

This changes the dynamics of the system because it’s completely self-contained and the whole experience exists around the user. If you are walking down the street, hiking in the mountains or walking down a trail with this thing attached to you, it will naturally follow with you without any special algorithms.

Audrow Nash: Can you tell me a bit about the leash, how it works, how it keeps constant tension?

Sergei Lupashin: When it’s hovering it doesn’t fly straight up; it flies at a small angle and it stays not above you but to the side. The leash is spring-loaded, so the Fotokite produces a bit of extra force to keep the tether under tension.

You can just point the Fotokite in the direction you want to launch it, but once it’s flying, how do you tell it to turn? How do you tell it to move around? We wanted to get away from the concept of having to use a joystick or your smart phone to do that. Inside the leash are electronics that connect to the Fotokite while it’s flying; to control it you hold down the button on the side of the leash and you rotate your wrist. That motion of your wrist – that motion of the leash – is translated into a command for the Fotokite.

Audrow Nash: What kind of commands can you give? Can you have it rotate to look around?

Sergei Lupashin: Yes. Right now there are just two modes of interface. One mode is in-phase rotation. For example, if I want to take a panorama, I would launch the Fotokite straight up and then I would hold down the first button and rotate my wrist. The Fotokite would then rotate in place and capture the full 360 panorama. The other mode lets you control the position of the Fotokite relative to you.

Audrow Nash: The angle?

Sergei Lupashin: Exactly. We usually speak in terms of ‘elevation’ and ‘orbit’. For example, if you look at the stars in the sky, a star has a certain elevation above the horizon. To control the elevation in our case, holding down a button while you move your wrist up and down will move the Fotokite either from a horizontal position to a vertical one (relative to you), or vice versa. It basically controls the vertical angle where it flies.

Moving your wrist in the horizontal plane will cause the Fotokite to orbit, meaning that it will slowly reorient itself around you. If you keep doing this motion, the Fotokite will complete a circle around you at a given elevation.

You can get really neat matrix-style shots of yourself. Or you can use it to do sophisticated shots, using the Fotokite like a flying steady-cam.

Audrow Nash: How long does it take to train someone to use the Fotokite?

The beauty of the system is that there is nothing active in this tether, so you can attach any string to the Fotokite and it will still work just fine.

Sergei Lupashin: It’s a different experience from traditional drones because the interface is so physical: you feel pretty much the smallest motions of the Fotokite in the air through the string.

We did a number of demos for both expert drone users and people who haven’t touched one before. Getting it to fly is surprisingly straightforward: you show someone how to do it, they’ll repeat the motions, and it will work immediately.

To get really unique shots and smooth video requires a bit of skill. The nice thing is, with the tether, you can use your own physical movements to control it and to keep it from crashing into things. It’s a lower stress experience than what you see with traditional drones.

Audrow Nash: Speaking of crashing into things, what happens if it bumps into an object? Or if someone runs into the tether, the tether becomes taught in a different direction, and that tension is released suddenly?

Sergei Lupashin: In terms of bumping into things, we have protective coverings that extend past the motors, so most of the time an object would bump into the protective coverings first. That helps to prevent crashes, and it also helps to give the user confidence in being around the Phi.

In terms of the tether getting caught in things, the beauty of the system is that there is nothing active in this tether, so you can attach any string to the Fotokite and it will still work just fine.

For example, if you’re filming the rooftop of your house and you’re trying to get over to the other side of it, you can actually fly the Fotokite over the rooftop and then get it such that the tether touches the edge so you can sling-shot it over. It will simply use that new fixed point as the new reference point, and this happens naturally.

Explained in words it sounds weird, but just imagine flying a kite where the lift is generated by the kite itself: if you grab the kite string, and someone pulls it away, it will still fly at the same angle – but relative to that new point.

Audrow Nash: Does this mean that you don’t really need the smart leash? Is it just for controlling the Fotokite, so that it rotates and you can change the vertical angle?

Sergei Lupashin: The smart leash is there to make the system complete. Most folks just want to use the system to capture a picture or video. We didn’t want to make them have to go find a string.

The leash is a convenience: it’s nicely built, it has a spring, and it has electronics that allow control.

The Phi’s arms fold up with the propellers on the inside so that you can put it into its tube-shaped carrying case. It’s about the size of a thermos, and you fit it into your backpack.

I should also mention that the Fotokite Phi folds, because in real life, transportation is a major issue. The Phi is pretty unique in that it has a lock mechanism that makes a satisfying click when it locks. And when you unlock it, the arms fold up with the propellers on the inside so that you can put it into its tube-shaped carrying case. It’s about the size of a thermos, and you fit it into your backpack.

Audrow Nash: And everything fits in there?

Sergei Lupashin: Yes, the leash and everything.

Audrow Nash: The tether is very nice from the perspective of controlling the drone. What are some other advantages of using tethers?

Sergei Lupashin: The tether wasn’t actually the original idea.

I was finishing my PhD and looking at different schemes for aerial systems. This was in Raff D’Andrea’s lab – he has been on your podcast as well. We were exploring some different approaches using gestures – with Kinnect for example. But all of these systems were based on machine vision, which is incredibly sensitive to the conditions you are operating in. Sunrise, lens flare, darkness, water – all of these things confuse the system.

The tether completely changed the dynamics of the conversation between the operator, the vehicle and the public. It makes this device much more acceptable in public.

So the question was: how do we get localization and interaction in the most robust way possible? That’s where the idea of the tether came from: it was originally a technical solution to let a flying vehicle figure out precisely where it is relative to you, without relying on sensitive systems like GPS or machine vision etc.

Then, when we made the first demo, it turned out to be a really elegant way to interact with the system. The tether completely changed the dynamics of the conversation between the operator, the vehicle and the public. I think this was actually one of the most exciting moments of this process, because as a technologist you don’t foresee it; you see the tether as a technical solution and nothing else. But then it turns out to also have all of these facets that are not technical, but rather about the experience, and how people see the product.

In the end, the tether changes the Fotokite from being another drone into something that is more of a companion flying device. It’s a very personal device … it’s more like a kite, and people treat it that way.

One parallel is to imagine being at the park and having your dog on a leash versus not on a leash: for some people it’s fine, but other people just get freaked out by dogs that are not leashed. I think we see some of that with drones from a privacy perspective. What we found is that having a tether changes the conversation and makes this device much more acceptable in public.

Audrow Nash: There’s accountability because you can see where the operator is?

Anyone – no technical background required – intuitively understands the chain of responsibility with this device.

Sergei Lupashin: Exactly. Anyone – no technical background required – intuitively understands the chain of responsibility with this device.

Audrow Nash: Can you tell me a bit about how this and similar technology has been used in journalism, for example the Fotokite Pro?

Sergei Lupashin: The original inspiration for the Fotokite came from aerial footage of the Bolotnaya Square demonstrations in Russia in 2011. It was after the federal elections, and it was a big demonstration right in the center of Moscow. The footage was captured pretty much by pure chance from a drone – quite a big drone with an SLR camera. There was this one image, a panorama really … it’s amazing how well it transmitted the scale and atmosphere of the event.

The people who took that footage were very lucky that they happened to have the right equipment; they were professionals so they could do it safely, and they happened to have the right permissions. But we’ve seen many other examples where people haven’t been able to get these perspectives and cover events like this as well as they could have been covered. For example, in Ferguson, Missouri where there was a no fly zone was imposed, which many believe was done to keep the media out.

We also found out that having a physical connection usually changes the regulatory aspect. For example, in Switzerland and France, after some conversation with the regulators we were able to get special rules for tethered devices that are much more permissive than traditional drones. From a regulatory perspective, the usual thought process is focused on safety, whereas privacy is more universal and not usually what they are basing rules on. From a safety perspective, in Zurich for example, it was prohibited for a while to fly drones commercially. The Fotokite was allowed based on the tether and specifically based on the idea that the tether restricts the height of the device.

Many regulators think of how much energy would be dissipated if the device falls in an uncontrollable fall, and there is a magic number of 66 joules … if you fall and it dissipates 66 joules then you are magically unsafe.

Audrow Nash: How much is 66 joules?

Sergei Lupashin: This is potential energy, so it’s Mass X Gravity X Height. Imagine a 6 kg bowling ball falling from about a meter …

It’s a safety margin. With the Fotokite’s tether you can restrict the length of the tether and thus the height, so you can guarantee that under no conditions are you going to exceed that safety limit.

Audrow Nash: So you can only extend to the length of the tether unless you can’t get high enough to possibly generate 66 joules on complete impact?

Sergei Lupashin: Yes, that’s right.

There are other aspects they look at, too, like system robustness. For example, how many subsystems or how many components do you have in your critical loop? How many subsystems are there such that if one of them fails you have an uncontrolled system or a catastrophic failure? In a traditional drone, GPS is usually in that critical loop, as is your radio system, and if you lose your GPS or radio you will crash into something. With the Fotokite, there is no GPS and if the radio cuts out, it will just fly in the same position.

Audrow Nash: How does it look for other countries with these exemptions? For example, do you believe the US will permit tethered drones to fly? Do you think they will give exemptions similar to Switzerland and France?

Sergei Lupashin: It’s very hard to predict which way the US regulations are going to go right now. If you look at the history of it, just over the past few months regulations were proposed that were extremely lenient and permissive. Most recently there has been a massive push over certain events … you’ve probably heard of the person shooting drones down over their property. So it’s really hard to predict.

It’s a challenge since all of this technology is new and people don’t quite know how to differentiate it. For example, what is a tethered drone? If you attach a fishing line to a DJI, is it now tethered? I kid you not that there are commercial products out there for sale that offer exactly this, and they promise to get you around regulations.

We are trying to be proactive and come up with commonsense and observable definitions of what it means to be tethered.

We are trying to be proactive and come up with commonsense and observable definitions of what it means to be tethered. For example, I really believe that the tether has to be loadbearing, meaning that under typical flight it should actually be under tension, and it should be rated for some sort of tension that responds to the vehicle.

Audrow Nash: For a hobbyist or someone that just wants to use the Fotokite Phi to take pictures of themselves, do these regulations mean anything outside of countries that have exemptions for tethered drones? Or is it only for commercial use and journalism that the regulations apply?

Sergei Lupashin: Regulations generally apply to commercial use, but there are exceptions specifically generally cities, populated centers, and in the US national parks. If you go for a hike to the Yosemite or Yellowstone National Park in the US, for example, you can’t use a drone right now. These are the kind of the frontlines where we’re going to see how consumer drones get regulated in the future.

Audrow Nash: Going back to the Phi, how does the tether affect battery life?

Sergei Lupashin: In the Pro we use the tether to supply power, so we can fly forever. In the Phi we couldn’t do that because of cost and complexity, so we use a standard one-port battery. The trick there is that, since you’re producing extra tension to keep the tether taut, you are wasting a tiny bit of battery life, but on the other hand, if you imagine how a kite actually uses the wind, you could be using a less than normal power to stay afloat.

The current prototypes fly for around 7-10 minutes. For the production units, we are aiming for 15 minutes of typical flight time. The battery is swappable in the field, so you always have the option of replacing it.

Audrow Nash: How did you decide to move from a journalism drone – the Fotokite Pro – to a consumer drone with Fotokite Phi?

Sergei Lupashin: With the Fotokite Pro we realized after talking to existing drone users that the tether has a unique advantage especially in the niche of live reporting. In journalism you typically want to operate next to people and next to something that’s happening, and you don’t want to add tension to that situation. It’s a very unique niche where the tether makes a huge difference. The powered tether is important because journalists can keep the device afloat and not worry about battery life.

But we always wanted to build something a wider reach, and a few months ago we finally decided it’s now or never, because everything is developing very quickly. The Phi is is a big experiment for us to see how well we can use the tether to build a new user experience.

A lot of people see the Phi for the first time and they think it’s just a quadrocopter on a string, but the deeper story is to look at the engineering behind it, using the tether as a different interface approach.

A lot of people see the Phi for the first time and they think it’s just a quadrocopter on a string, but the deeper story is to look at the engineering behind it, using the tether as a different interface approach.

Audrow Nash: Is this a way of addressing the interaction bottleneck with robotics technology?

Sergei Lupashin: That’s right. Have you tried reprogramming your alarm clock lately? [laughs]

In robotics labs we tend to come up with ridiculously complex systems. I’m sure they can do a lot in principle, but they are very difficult to interact with. I think this somehow echoes with many robotics products that have already come out. An example of that is in Japan when the Fukushima incident happened. Arguably Japan has some of the most advanced robotics, especially for search and rescue, anywhere in the world. But they really struggled to make a difference in that situation. And I think a lot of problems are because of interaction, because of training, and because of the complexity of the systems.

The inspiration for the Phi is really to try to cut across that and come up with a smooth and low-friction user experience, where even someone who has never touched robotics could be shown how to use this device and they could naturally take it, use it themselves, and feel confident and empowered by it.

Audrow Nash: Thank you.

Sergei Lupashin: Thank you.

All audio interviews are transcribed and edited for clarity with great care, however, we cannot assume responsibility for their accuracy.

The EU-funded Collective Cognitive Robotics (CoCoRo) project has built the world’s largest swarm of 41 autonomous underwater vehicles (AVs) that show collective cognition. Throughout the first half of 2015 – The Year of CoCoRo – a new video on the latest stage in its development has been uploaded every week, with dozens online to date and more to come! This article provides some insights and background about some of the videos already online.

Carried out by an interdisciplinary and international team of scientists from Austria, Italy, the UK, Belgium and Germany, the CoCoRo project ran from 2011-2014 and has its own YouTube playlist. It offers a novel information platform for the scientific community and anyone interested in how new high-end technologies are developed and what impact they could have on people’s lives.

The footage tracks the development of this unique, autonomous swarm and also demonstrates how it gained the necessary self-awareness to solve tasks such as search missions on the seabed.

In the videos already online, three different autonomous underwater robots, designed and produced for the project, are introduced: very agile and fast Jeff robots, which search the waterbed, and smaller Lily robots, functioning as communicators to relay the information found by Jeffs to the third robot type: a base-station which floats on the water surface and is able to pass information to scientists on the ground.

The videos also show many different experiments, showcasing the broad functionality of the autonomous swarm. They demonstrate how novel, bio-inspired algorithms, developed by the team, give the swarm a form of self awareness to provide a much broader knowledge base than is in the possession of each single member. This enables the swarm to make collective decisions.

Thus, the videos demonstrate the functionality of the swarm, in collective search missions, as well as the abilities and the specialties and strengths of the different robot types. Below, we look at some of the highlights of this research.

Autonomously driven camera agents, exploring seas, rivers and ponds

The Jeff and Lily robots were tested as autonomous diving robots with cameras mounted to collect material on the underwater ecosystem. Their recorded diving trips provide lively insights into the underwater world: the sea, mountain lakes, ponds and rivers. Although not the main focus of the project, this work developed into a set of interesting spin-off experiments. It is always nice to discover that a tool can also be used something other than what it was originally designed for. In the first set of experiments, an underwater camera was mounted on a Lily robot. The setup was initially tested in a small fishpond, then in a larger Austrian lake and, finally, some mad scientists even threw the poor robot into a whitewater river!

Once it was discovered that the robots could be used as autonomous camera agents, cameras were also mounted on the Jeffs and the research team moved on to larger lakes and more complex habitats to get an inside view.

Blue light and electric sensing for novel AUV underwater communication

The CoCoRo team established a new approach to underwater communication that is showcased in the videos.

In contrast to the majority of underwater swarms, these robots don’t communicate using sonic or echo technology but instead make use of blue-light LEDs, WLAN and potential electric fields. Blue-light blinks are used to keep the swarm together and in the vicinity of the moving base station. Because of this “confinement,” the radio-controlled base-station can pull a whole swarm of Lily robots behind it, much like a tail. In larger water bodies, it is important to confine the robots into specific areas because, if agents are to work efficiently, the swarm normally requires a minimum of connectivity that is achieved only with a critical density; if they’re not confined to a controlled area, robots could get lost and the density could fall below the critical level. Thus, confinement was identified as a key function.

“Electric sense” (coupled potential electric fields) is another important CoCoRo feature. An electrode was placed underwater, beneath the CoCoRo surface station, to generate a pulsing electric field. Jeff robots, with electrodes attached to their outer hulls, are able to sense such fields. In this way, it’s possible to confine the robots to a specific area, around the base station, so that they don’t go astray. Electric-field confinement was tested in a pool, under laboratory conditions, and then in the Italian harbor of Livorno.

Self-charging mechanisms guarantee long-term autonomy in energy

An important goal of the CoCoRo project was to develop an underwater swarm able to achieve long-term autonomy in respect of energy. To this end, a special docking/undocking mechanism was constructed for Jeff robots, on the base station. Later versions of these robots that run out of power will not only be able to dock or undock autonomously there, but also recharge. Several videos demonstrate this docking mechanism in action, both in a pool and in the Mediterranean.

Collective decision making on underwater search missions in highly fragmented areas

Another important aspect of the CoCoRo swarm is that it is able to make collective decisions, the result of a set of bio-inspired algorithms developed for it. To test this ability, a set of collective choice experiments was performed.

The Lily swarm, as a whole, was tasked with choosing a global magnetic optimum over several local optima. To make the experiment even trickier, and the results more clearly interpretable, the scientists constructed a T-Maze offering only a binary choice. In another experiment a similar task was performed in an open field. In each of these settings, the swarm reached a clear-cut decision in favor of the global optimum. In CoCoRo, the ability to make a decision is a property of the collective, not of the individual.

However, habitats are often more structured than a T-maze. To test the capabilities of Jeff robots in highly structured environments, area coverage was achieved through autonomous motion behavior; a specific random walk, with the robots browsing through the habitat, performing a simple program named “correlated random walk with obstacle avoidance.” This consists of a straight-forward motion alternated with infrequent, randomly triggered turns and collision avoidance based on blue-light emission and the robot’s sensing of its reflection. As a result, the first robot is able to traverse the habitat relatively quickly, and subsequent robots even faster. The experiments demonstrate that, here, scalability is key in generating a viable robot swarm. To gain further insight into how Jeff robots navigate through highly fragmented areas, the researchers equipped them with cameras to film their behavior.

In order to further complicate the Jeff robots’ task of searching and navigating, the team constructed a fragmented habitat in a pool, with four compartments separated by medium-height walls. Only one of these contained a magnetic/metallic object, acting as a search target. To complete the experiment, the random-walk based motion program was occasionally interrupted by “jump-over-the-wall” behavior. This allowed the test robot to switch between compartments when it detected a near-collision event via its blue-light LEDs.

The autonomous robot observes its internal magnetic sensor in order to identify whether it is close to the magnetic/metallic target. When it is, it stops, descends and switches on all of its LEDs to mark the spot.

In another experimental video, the scientists demonstrate the use of the search algorithm in pools with increasing volumes of water and with a number of Jeff robots. Building on the previous experiment, social swarm behavior is exhibited as the robots attract each other to the target after they have found it. In a preliminary experiment, for the first time the robots went deeper than two meters, although software bugs were an issue. However, these late-night experiments brought to light crucial insights and allowed the team to develop the more complex search scenarios that will feature in the second half of the Year of CoCoRo.

In another extension of the scenario, a swarm of Lily robots was introduced, with one Lily emulating the behavior of the base station on the water’s surface. A searching Jeff robot on the ground first autonomously looks for a magnetic target. When it finds this, it stops and switches on its vertical blue-light and red LEDs. This attracts some Lily robots browsing near the surface. They pick up the signal from the ground and recruit other Lily robots with their horizontal blue-light LEDs. This attracts even more Lily robots, forming a positive feedback loop through the growing aggregation of robots. Ultimately, all the Lily robots meet at the target spot as well as the one emulating the surface station.

What’s next in The Year of CoCoRo?

In the second half of The Year of CoCoRo, the videos will emphasize more complex waterbed search tasks, showing several different approaches to this. In addition, they will focus on swarm-level self-awareness, internal homeostatic self-regulation and self-repair. The CoCoRo team will also demonstrate shoaling behavior, how the swarm can communicate, even in murky waters, and that it’s not tricked easily, not even by its own mirror image; it knows whether what it “sees” is a reflection of itself or another robot swarm. Aside from scientific experiments, further videos will cover special CoCoRo events, providing some humorous insights into EU-project driven research. Some of these will include: an exhibition at CEBIT (a consumer electronics fair) overnight project workshops and overview videos to round off the big picture: The Year of CoCoRo.

CoCoRo evolves into subCULTron

The experiments and developments shown in The Year of CoCoRo are being fed into subCULTron, a follow-up project that has already started. Here, an even larger swarm of robots – novel types with more bio-inspired algorithms – are being developed. Leading scientists from other projects, including CADDY and ANGELS have joined the consortium. This CoCoRo offspring is planning missions in the Venice lagoon, as well as in a complex, structured, aquatic mussel farm. In these environments, the water is deeper and murky, and the habitat even more fragmented, posing ever-greater challenges for this novel collective system.

If you liked this article, you may also be interested in:

• 3’600-strong underwater robot sensor network returns 1’000’000th measurement, has scientists craving for more
• Thousand-robot swarm self-assembles into arbitrary shapes
• Surgical micro-robot swarms: Science fiction, or realistic prospect?
• Underwater Dreams: The story of undocumented teens who win underwater robot competition
• Crowdsourcing new strategies for cancer treatment: Towards swarming nanobots
• Robots Podcast: Termite-Inspired Construction

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

The campaign has also unlocked 12 stretch goals including:

• Kids programming environment
• Special Kids pack (i.e Autism)
• Side tray accessory with USB charging
• Expressions pack
• Elder pack
• Hackathon
• Black color
• Memory extension to 32 GB
• Air quality sensing module
• Easypath application to create your own smart applications
• IBM Watson integration

And Blue Frog Robotics has also announced some accessories including:

• Standard motorized arms
• Pico Projector Arm
• Docking station for charging

Developed by the French company Blue Frog Robotics, BUDDY beat his crowdfunding goal ($100,000) in a day, and has been filmed and written about across the world.

BUDDY has a new (second) home

BUDDY enjoyed an enthusiastic welcome on his first visit to the US in August to meet press, investors and fans. He’ll be a regular visitor as Blue Frog Robotics announced the opening of its North American offices in Boston and San Francisco .

Videos

“Buddy is a really, really, ridiculously cute family robot” – Lucas Matney, TechCrunch

“Buddy the robot protector looks like R2-D2’s first cousin” – Stephen Beacham, CNET TV

“With Jibo and now Buddy, Boston is becoming a social-robot mecca”  – David Harris, Boston Business Journal

“Meet Buddy: the Stars Wars-Inspired Robot”< – CRN

“Robot pet-sitters?”  – Scott Kirsner, The Boston Globe

“Buddy robot snubs creator” – Dan Simmons, BBC news

“Buddy the robot is ‘more useful than an iPhone’”
– Anthony Cuthbertson, International Business Times

Articles

“BUDDY, A Crowdfunded Robot And Platform” – Hubert Nguyen – Ubergizmo

“Buddy whisks around on wheels and casters while JIBO, another social robot option, swivels harmlessly on your desk or floor” – Dominic Basulto, The Washington Post

“Buddy marks an advance in the progression of agents from Siri to Amazon Echo, as it moves and interacts proactively” – Ross Rubin, Venture Beat

“Downloading apps on your own personal robot may become as common as downloading apps on your smartphone”  – Cadie Thompson, Business Insider

“Rolling Buddy robot may just kill you with cuteness”  – Lance Ulanoff, Mashable

Rodolphe Hasselvander, creator of BUDDY, says: “We are incredibly overwhelmed and thankful for the love and support BUDDY has received over the past month. The reaction from people is beyond even my wildest of expectations.”

Flying Fotokite close up

Zurich-based robotics company Perspective Robotics this week unveils Fotokite Phi, their first consumer targeted, affordable, accessible, tethered flying camera. The Fotokite Phi is available now for pre-order on Indiegogo for $349 USD.

https://www.youtube.com/watch?v=aglTWdI-4Bo

The story behind Fotokite

Inspired by drone operators during the Russian protests in 2011, Perspective Robotics’ CEO Sergei Lupashin set out to make a drone that is safe and easy to use. The result is the Fotokite, a tethered user-friendly quadcopter, with a unique take on safety for both the operator and the people nearby. The Fotokite Phi is based on the same technology that Lupashin demo’ed on the TED stage in 2014, and that is also currently being used by major news outlets, such as the BBC, for their broadcast coverage and special programming.

Key benefits include:

Instant launch, intuitive gesture control

Fotokite is the only drone on the market that doesn’t rely on remote piloting or GPS, making for a simpler, more intuitive, user experience. To launch the Fotokite Phi, the user simply points it in the direction they want it to go and gives the device a quick shake. The onboard GoPro is powered by the Phi and automatically turns on when flying. The Fotokite’s core algorithms – developed by Lupashin while he worked on his PhD at the Flying Machine Arena at ETH Zurich, Switzerland – are protected by a patent application and enable the device to fly itself, controlled by simple gestures, on the end of the tether, with no need for a remote control or GPS.

Foldable and portable

The Fotokite Phi easily fits into a backpack or suitcase. It weighs 12 ounces, including the GoPro 3/3+/4 camera and battery, and is the lightest GoPro-carrying quadcopter on the market. The Fotokite Phi folds into a compact carrying case (about the size of a two liter soda bottle) and can easily fit in a backpack or suitcase for people traveling with it. The Fotokite Phi comes with a 26 foot leash included and a removable battery that charges directly through a USB port.

Safer for users and the people around them

If the Fotokite Phi detaches from the tether, the device is programmed to detect a lack of tension and float slowly to the ground, instead of flying away. In addition, the Fotokite’s soft propellers are safe to the touch.

Fotokite Phi folded, half in its tube

Accountability

The tether makes it clear to bystanders who’s controlling the device, allowing for accountable aerial photography. To this end, Fotokite has secured special exemptions in Switzerland and France to be flown near crowds. Fotokite is currently working towards acquiring the same permission from the FAA in the US.

Fotokite at a museum

Flight Unit

Propellers : Soft Plastic 6,5 inch Fotokite Prop

Weight : 300g (excluding GoPro Camera), 350g (including GoPro camera)

Battery : Li Po Battery (1000 Ah, 11.1Wh), 3 cells

Flight time : We are aiming for 15 minutes

Camera : Go Pro 3 / 3+ / 4

Charger : USB 3C Charging cable

Dimensions : 90mm height, 350mm diameter, 170mm rotor diameter

CPU : ARM Cortex Processor

Sensors : IMU, no GPS

Motors : 1400 Kv Brushless

Smart-Leash

8m cord, self retracting

Dimensions : 40mm height, 90mm diameter

Sensors : IMU

Case

Dimensions : 90mm x 300mm

Weight : 150g

China is the world’s largest consumer market of industrial robots for the second consecutive year, according to statistics released by the China Robot Industry Alliance (CRIA). Sales in China increased by 54.6% in 2014 to around 57,000 units, 25% of the global total. Data shows that nearly 17,000 units were made in China with a value of $474m, an increase of 60% from 2013.

Various research reports are predicting that more than 250,000 industrial pick and place, painting and welding robots will be purchased and deployed in China by 2019. That figure represents more than the total global sales of all types of industrial robots in 2014! The Chinese government is encouraging the development of an in-country robotics industry because, currently, three-quarters of all robots purchased are from off-shore companies (albeit some with manufacturing and assembly facilities in China).

We have been able to identify 47 Chinese companies and five startups that call themselves industrial robot makers, and another 26 which offer to provide integration services and speciality equipment. 34 more provide ancillary services, sensors and components to the robot makers. Overall, 107 Chinese companies are involved in industrial robotics. Many of these new industrial robot makers are producing products that, because of quality, safety and design regulations, will only be acceptable to the Chinese market.

In addition to growth in Chinese industrial robotics, progress in the service sector is also healthy. A shining example of the 48 mostly new service robotic companies on the map is Shenzhen DJI Innovations, of quadcopter fame. DJI is projected to sell devices worth $1bn in 2015.

Two other notable growth areas in the service sector are materials handling and the production of unmanned air, sea and ground devices for China’s developing space, military and defense industries.

The consumer sector is also growing: robotic vacuums and personal/social robots are examples. Last “Singles Day,” a brand new shopping holiday in China, Alibaba sold over 70,000 Ecovacs robotic vacuum cleaners!

The drivers propelling this boom are many and varied:

• Government mandates and political encouragement to develop the industry domestically and, ultimately, to export products
• Low-cost loans and factory incentives
• Tax credits for robot users and also to robot makers that employ local workers
• Engineering talent spewing out from Chinese technical universities and research facilities
• Rising wages
• A diminishing factory-age work force
• A rapidly aging work force, hampered by the one-child policy of past regimes
• The high cost of training and housing for a short-term transient work force
• Ramping up of auto makers to satisfy domestic demand and to improve quality and produce Chinese cars for export — for China to have competitive cars in the international marketplace (not just price-competitive), they have to improve quality, consistency and technology — and robotics is enabling them to do so
• Serious investment in automation and robotics from companies, such as Foxconn and Apple, that manufacture their goods in China
• A growing middle and upper class with disposible income for high-tech devices

The Robot Report and the research team at Robo-STOX have been able to identify 194 companies that make or are directly involved in making robots in China. The CRIA and other sources, believe the number to be closer to 400.

The Robot Report’s Global Map is limited by our own research capabilities, language translation limitations, and scarcity of information about robotics companies and their websites and contact people. We could use your help in adding to the map. Please send companies that we have missed (or are new) to info@therobotreport.com.

You can explore the map online and filter it in a variety of ways. Use Google’s directional and +/- markers on the left of the map to navigate, enlarge, and hone in on an area of interest (or double click near where you want to enlarge). Click on one of the colored markers to get a pop-up window with the name, type, focus, location and a link to the company’s website.

[Note: the map shows a single entry for the company headquarters regardless how many branches, subsidiaries and factory locations that company might have.]

The Filter pull-down menu lets you choose any one of the seven major categories: (1) Industrial robot makers; (2) Service robots used by corporations and governments; (3) Service robots for personal and private use; (4) Integrators; (5) Robotic start-up companies; (6) Universities and research labs with special emphasis on robotics; and (7) Ancillary businesses providing engineering, software, components, sensors and other services to the industry.

As can be seen from the map at the top of the page, most all of the companies and educational facilities are located on the East Coast or in Central China; very few are located in the Northeast or in Western China.

The research firms forecasting dramatic growth for the domestic Chinese robotics industry are also predicting very low-cost devices. Their reports are contradicted by academics, roboticists and others who point out that there are so many new robot manufacturing companies in China that none will be able to manufacture thousands of robots per year and thus benefit from scale. Further, many of the components that comprise a robot are intricate and costly, e.g., reduction gears from Nabtesco, Harmonic Drive and Sumitomo (all Japanese companies). Although a few of the startups are attempting to make reduction gears and other similar devices, the lack of these component manufacturers in China may put a cap on how low costs can go and on how much can be done in-country for the time being. Another negative is that all but auto manufacturers have short product cycles requiring any robots on the line to be extremely flexible. Worker flexibility is still crucial in Chinese manufacturing.

In the chart below, the 194 Chinese companies are tabulated by their business type and area of focus.

Again, we request your help adding to the map and making it as accurate and up-to-date as possible. Please send robotics-related companies that we have missed (or new ones) to info@therobotreport.com.

Savioke Relay Dash delivery robot. Source: Savioke

Leading hotel operator the InterContinental Group is introducing delivery robots at its Crowne Plaza San Jose-Silicon Valley property. The robots, made by local startup Savioke, will deliver snacks, toothbrushes and other amenities to guests in their rooms.

The success of the new service, announced by the hotel group on Monday, will determine whether robot delivery will be introduced in other Crowne Plaza branded properties. The brand has almost 400 hotels in 65 locations.

Named Dash, the Crowne Plaza’s new autonomous service has been created by Savioke, specialists in robot solutions for the hospitality industry. The system is based on the company’s latest autonomous service, Relay. Approximately 3-feet tall and weighing less than 100 pounds, Dash is designed to travel at a human walking pace, can independently navigate between floors and summon the hotel elevator using a wifi connection.

Savioke unveiled its first delivery robot, SaviOne, almost a year ago and announced a new pilot scheme at the Aloft Hotel in Cupertino, California, which became the first major hotel brand to hire a robot for both front and back of house duties.

Savioke’s new partnership with the InterContinental Group, will utilise the latest version of its autonomous delivery service featuring automatic docking, improved autonomy, and an all new design enabling Savioke to scale in response to demand.

“With more than 300 guest rooms, this is the largest hotel to use our robot technology,” said Steve Cousins, CEO of Savioke. “We’re excited to see the updated version of our Relay robot find a home at this Crowne Plaza hotel.”

With its location in Milpitas, in the very centre of Silicon Valley, it’s apt that the Crowne Plaza Hotel is showcasing some of the cutting edge talent that is so associated with this part of the world.

“Located in the heart of Silicon Valley, our hotel is making use of the best technology innovation that Silicon Valley has to offer,” said Crowne Plaza General Manager, Winnie Kwok.