The hype cycle representation of the robotics field based on the general interest since its inception obtained from a joint review of publications, conferences, events and solutions. From “Dissecting Robotics — historical overview and future perspectives”.

Robotics, like many other technologies, suffered from an inflated set of expectations resulting in a decrease of the developments and results during the 90s. Over the last years, several groups thought that flying robots, commonly known as drones, would address these limitations however it seems unlikely that the popularity of these flying machines will drive and push the robot growth as expected. This article aims to summarize traditional techniques used to build and program robots together with new trends that aim to simplify and enhance the progress in the field.

Building robots

It’s a rather popular thought that building a robot and programing its behavior remain two highly complicated tasks. Recent advances in adopting ROS as a standardized software framework for developing robot applications helped with the latter, however building a robot remains a challenge. The lack of compatible systems in terms of hardware, the non existing marketplace of reusable modules, or the expertise required to develop the most basic behaviors are some of the few listed hurdles.

The integration-oriented approach
Robots are typically built by following the step-by-step process described below:

1. Buy parts: We typically decide on what components our robot will need. A mobile base, a range finder, a processing device, etc. Once decided we fetch those that match our requirements and proceed towards integration.

2. Integration: Making different components speak to each other and cooperate towards achieving the end goal of the robot. Surprisingly, that’s where most of our time is spent.

3. “build the robot”: Assembling all of the components into joints and mechanically linking them. This step might also get executed together with step

4. Programming the robot: Making the robot do what it’s meant to do.

5. Test & adapt: Robots are typically programmed in predictable scenarios. Testing the pre-programmed behavior in real scenarios is always critical. Generally, these tests deliver results that indicate where adaptations are needed, which in many cases pushes de process of building a robot down to step 2 again, integration.

6. Deploy: Ship it!

The “integration-oriented” approach for building a robot.

It’s well understood that building a robot is a technically challenging task. Engineers often face situations where the integration effort of the robot, generally composed by diverse sub-components, supersedes many other tasks. Furthermore, every hardware modification/adaptation while programming or building the robot demands further integration.

This method for building robots produces results that become obsolete within a short period.

Moreover, modules within the robots aren’t reusable in most of the cases since the integration effort makes reusability an incredibly expensive (manpower-wise) and time-consuming task.

The modular approach

The existing trend in robotics is producing a significant number of hardware devices. Although there’s an existing trend towards using the Robot Operating System (ROS), when compared to each other, these components typically consist of incompatible electronic components with different software interfaces.

Now, imagine building robots by connecting interoperable modules together. Actuator, sensors, communication modules, UI devices,… provided everything interoperates together, the whole integration effort could be eliminated. The overall process of building robots could be simplified and the development effort and time will be reduced significantly.

Comparison between the “integration-oriented” and the “modular” approaches for building robots.

Modular components could be reused among robots and that’s exactly what we’re working on with H-ROS, the Hardware Robot Operating System.
H-ROS is a vendor-agnostic infrastructure for the creation of robot modules that interoperate and can be exchanged between robots. H-ROS builds on top of ROS, the Robot Operating System, which is used to define a set of standardized logical interfaces that each physical robot component must meet if compliant with H-ROS.

Programming robots

The robotics control pipeline

Traditionally, the process of programming a robot for a given task T is described as follows:
Observation: Robot’s sensors produce measurements. All these measurements receive the name of “observations” and are the inputs that the robot receives to execute task T.

State estimation: Given the observations of step 1, we describe the robot’s motion over time by inferring a set of characteristics of the robot such as its position, its orientation or its velocity. Obviously, mistakes in the observations will lead to errors in the state estimation.

Modeling & Prediction: Determine the dynamics of the robot (rules for how to move it around) using a) the robot model (typically the URDF of the robot in the ROS world) and b) the state estimation. Similarly to what happened with the previous step, errors in “state estimation” will impact the results obtained in this step.

Planning: this step determines the actions required to execute task T and uses both the state estimation and the dynamical model from previous steps in the pipeline.

Low level control: the final step in the pipeline consists of transforming the “plan” into low level control commands that steer the robot actuators.

The traditional “robotics control pipeline”

Bio-inspired techniques

Artificial Intelligence methods and, particularly, bio-inspired techniques such as artificial neural networks (ANNs) are becoming more and more relevant in robotics. Starting from 2009, ANNs gained popularity and started delivering good results in the fields of computer vision (2012) or machine translation (2014). Nowadays, these fields are completely filled by techniques that simulate the neural/synaptic activity of the brain of a living organism.

During the last years we have seen how these techniques have been translated to robotics for tasks such as robotic grasping (2016). Our team has been putting resources into exploring these techniques
that enable to train a robotic device in a manner conceptually similar to the mode in which one goes about training a domesticated animal such as a dog or cat.

Training robots end-to-end for a given task. This integrated and bio-inspired approach conflicts with the traditional robotics pipeline, however it’s already showing promising results of behaviors that generalize.
We are excited to share that it’s within our expectations to see more active use of these bio-inspired techniques. We are confident that its use will drive innovations with high impact for robotics and we hope to contribute by opening part of our work and results.

Programming robots versus training robots. This image pictures the traditional robotics approach named as the “robotics control pipeline” and the new “bio-inspired” approach that makes use of AI techniques that simulate the neural/synaptic activity of the brain.

The roboticist matrix

All these new approaches for both building and programming robots bring a dilemma to roboticists. What should they focus on? Which approach should they follow for each particular use case? Let’s analyze the different combinations:

The roboticist matrix presents a comparison between traditional and new approaches for building and programming robots.

Integration-oriented + robotics control pipeline:
This combination represents the “traditional approach” in all senses. It’s the process that most robot solutions use nowadays in industry. Integrated robots that typically belong to a single manufacturer. Such robots are programmed in a structured way to execute a well defined task. Typically achieving high levels of accuracy and repeatability. However, any uncertainty in the environment will typically drive the robot to fail on its task. Expenses related to develop such systems are typically in the range of 10.000–100.000 € for the simplest behaviors and an order of magnitud above for the more complex tasks.

Integration-oriented + bio-inspired:
Behaviors that evolve, but with strong hardware constraints and limitations. Traditional robots enhanced with bio-inspired approaches. Robots using this combination will be able to learn by themselves and adapt to changes in the environment however any modification, repurpose or extension within the robot hardware will require big integration efforts. The expenses for developing these robots are similar to the ones presented for the “traditional approach”.

Modular + robotics control pipeline:
Flexible hardware with structured behaviors. These robots will be built in a modular way. Building, repairing and/or repurposing these robots will be extremely affordable when compared to traditional robots (built with the integration-oriented approach), we estimate an order of magnitude less (1.000–10.000 €). Furthermore, modularity will introduce new opportunities for these robots.

Modular + bio-inspired:
This combination represents the most innovative one and has the potential to disrupt the whole robotics market changing both the way we build and program/train robots. Yet it’s also the most immature one.
Similar to the previous approach group, our team foresees that the expenses for putting together these robots can also be reduced when compared to the more traditional approaches. We estimate that building and training these robots should range in terms of expenses from 1.000 to 10.000 € for simple scenarios and up to 50.000 € for the more elaborated ones.

Our path towards the future: modular robots and H-ROS

A modular robot built using H-ROS compatible components.

The team behind Erle Robotics is proud to announce that together with Acutronic Robotics (Switzerland), Sony (Japan) is now also pushing the development of H-ROS, the Hardware Robot Operating System. A technology that aims to change the landscape of robotics by creating an ecosystem where hardware components can be reused among different robots, regardless of the original manufacturer. Our team strongly believe that the future of robotics will be about modular robots that can be easily repaired and reconfigured. H-ROS aims to shape this future. Sony’s leadership and vision in robotics is widely recognized in the community. We are confident that, with the addition of Sony as a supporter, our present innovations will spread even more rapidly.

Our team is focused in exploring these new opportunities and will introduce some results this week in Vancouver during ROSCon. Show your interest and join us in Canada!

Image: Ryan Etter

Robotics is said to be the next technological revolution. Many seem to agree that robots will have a tremendous impact over the following years, and some are heavily betting on it. Companies are investing billions buying other companies, and public authorities are discussing legal frameworks to enable a coherent growth of robotics.

Understanding where the field of robotics is heading is more than mere guesswork. While much public concern focuses on the potential societal issues that will arise with the advent of robots, in this article, we present a review of some of the most relevant milestones that happened in robotics over the last decades. We also offer our insights on feasible technologies we might expect in the near future.

Copyright © Acutronic Robotics 2017. All Rights Reserved.

Pre-robots and first manipulators

What’s the origin of robots? To figure it out we’ll need to go back quite a few decades to when different conflicts motivated the technological growth that eventually enabled companies to build the first digitally controlled mechanical arms. One of the first and well documented robots was UNIMATE (considered by many the first industrial robot): a programmable machine funded by General Motors, used to create a production line with only robots. UNIMATE helped improve industrial production at the time. This motivated other companies and research centers to actively dedicate resources to robotics, which boosted growth in the field.

Sensorized robots

Sensors were not typically included in robots until the 70’s. Starting in1968, a second generation of robots emerged that integrated sensors. These robots were able to react to their environment and offer responses that met varying scenarios.

Relevant investments were observed during this period. Industrial players worldwide were attracted by the advantage that robots promised.

Worldwide industrial robots:  Era of the robots

Many consider that the Era of Robots started in 1980. Billions of dollars were invested by companies all around to world to automate basic tasks in their assembly lines. Sales of industrial robots grew 80% above the previous years’.

Key technologies appeared within these years: General internet access was extended in 1980; Ethernet became a standard in 1983 (IEEE 802.3); the Linux kernel was announced in 1991; and soon after that real-time patches started appearing on top of Linux.

The robots created between 1980 and 1999 belong to what we call the third generation of robots: robots that were re-programmable and included dedicated controllers. Robots populated many industrial sectors and were used for a wide variety of activities: painting, soldering, moving, assembling, etc.

By the end of the 90s, companies started thinking about robots beyond the industrial sphere. Several companies created promising concepts that would inspire future roboticists. Among the robots created within this period, we highlight two:

1. The first LEGO Mindstorms kit (1998): a set consisting of 717 pieces including LEGO bricks, motors, gears, different sensors, and a RCX Brick with an embedded microprocessor to construct various robots using the exact same parts. The kit allowed the learning of  basic robotics principles. Creative projects have appeared over the years showing the potential of interchangeable hardware in robotics. Within a few years. the LEGO Mindstorms kit became the most successful project that involved robot part interchangeability.
2. Sony’s AIBO (1999): the world’s first entertainment robot. Widely used for research and development, Sony offered robotics to everyone in the form of a $1,500 robot that included a distributed hardware and software architecture. The OPEN-R architecture involved the use of modular hardware components — e.g. appendages that can be easily removed and replaced to customize the shape and function of the robots — and modular software components that could be interchanged to modify their behavior and movement patterns. OPEN-R inspired future robotic frameworks, and minimized the need for programming individual movements or responses.

Integration effort was identified as one of the main issues within robotics, particularly related to industrial robots. A common infrastructure typically reduces the integration effort by facilitating an environment in which components can be connected and made to interoperate. Each of the infrastructure-supported components are optimized for such integration at their conception, and the infrastructure handles the integration effort. At that point, components could come from different manufacturers (yet when supported by a common infrastructure, they will interoperate).

Sony’s AIBO and LEGO’s Mindstorms kit were built upon this principle, and both represented common infrastructures. Even though they came from the consumer side of robotics, one could argue that their success was strongly related to the fact that both products made use of interchangeable hardware and software modules. The use of a common infrastructure proved to be one of the key advantages of these technologies, however those concepts were never translated to industrial environments. Instead, each manufacturer, in an attempt to dominate the market, started creating their own “robot programming languages”.

The dawn of smart robots

Starting from the year 2000, we observed a new generation of robot technologies. The so-called fourth generation of robots consisted of more intelligent robots that included advanced computers to reason and learn (to some extend at least), and more sophisticated sensors that helped controllers adapt themselves more effectively to different circumstances.

Among the technologies that appeared in this period, we highlight the Player Project (2000, formerly the Player/Stage Project), the Gazebo simulator (2004) and the Robot Operating System (2007). Moreover, relevant hardware platforms appeared during these years. Single Board Computers (SBCs), like the Raspberry Pi, enabled millions of users all around the world to create robots easily.

The boost of bio-inspired artificial intelligence

The increasing popularity of artificial intelligence, and particularly neural networks, became relevant in this period as well. While a lot of the important work on neural networks happened in the 80’s and in the 90’s, computers did not have enough computational power at the time. Datasets weren’t big enough to be useful in practical applications. As a result, neural networks practically disappeared in the first decade of the 21st century. However, starting from 2009 (speech recognition), neural networks gained popularity and started delivering good results in fields such as computer vision (2012) or machine translation (2014). Over the last few years, we’ve seen how these techniques have been translated to robotics for tasks such as robotic grasping. In the coming years, we expect to see these AI techniques having more and more impact in robotics.

What happened to industrial robots?

Relevant key technologies have also emerged from the industrial robotics landscape (e.g.: EtherCAT). However, except for the appearance of the first so-called collaborative robots, the progress within the field of industrial robotics has significantly slowed down when compared to previous decades. Several groups have identified this fact and written about it with conflicting opinions. Below, we summarize some of the most relevant points encountered while reviewing previous work:

• The Industrial robot industry :  is it only a supplier industry?
  For some, the industrial robot industry is a supplier industry. It supplies components and systems to larger industries, like manufacturing. These groups argue that the manufacturing industry is dominated by the PLC, motion control and communication suppliers which, together with the big customers, are setting the standards. Industrial robots therefore need to adapt and speak factory languages (PROFINET, ETHERCAT, Modbus TCP, Ethernet/IP, CANOPEN, DEVICENET, etc.) which for each factory, might be different.
• Lack of collaboration and standardized interfaces in industry
  To date, each industrial robot manufacturer’s business model is somehow about locking you into their system and controllers. Typically, one will encounter the following facts when working with an industrial robot: a) each robot company has its own proprietary programming language, b) programs can’t be ported from one robot company to the next one, c) communication protocols are different, d) logical, mechanical and electrical interfaces are not standardized across the industry. As a result, most robotic peripheral makers suffer from having to support many different protocols, which requires a lot of development time that reduces the functionality of the product.
• Competing by obscuring vs opening new markets?
  The closed attitude of most industrial robot companies is typically justified by the existing competition. Such an attitude leads to a lack of understanding between different manufacturers. An interesting approach would be to have manufacturers agree on a common infrastructure. Such an infrastructure could define a set of electrical and logical interfaces (leaving the mechanical ones aside due to the variability of robots in different industries) that would allow industrial robot companies to produce robots and components that could interoperate, be exchanged and eventually enter into new markets. This would also lead to a competitive environment where manufacturers would need to demonstrate features, rather than the typical obscured environment where only some are allowed to participate.

The Hardware Robot Operating System (H-ROS)

For robots to enter new and different fields, it seems reasonable that they need to adapt to the environment itself. This fact was previously highlighted for the industrial robotics case, where robots had to be fluent with factory languages. One could argue the same for service robots (e.g. households robots that will need to adapt to dish washers, washing machines, media servers, etc.), medical robots and many other areas of robotics. Such reasoning lead to the creation of the Hardware Robot Operating System (H-ROS), a vendor-agnostic hardware and software infrastructure for the creation of robot components that interoperate and can be exchanged between robots. H-ROS builds on top of ROS, which is used to define a set of standardized logical interfaces that each physical robot component must meet if compliant with H-ROS.

H-ROS facilitates a fast way of building robots, choosing the best component for each use-case from a common robot marketplace. It complies with different environments (industrial, professional, medical, …) where variables such as time constraints are critical. Building or extending robots is simplified to the point of placing H-ROS compliant components together. The user simply needs to program the cognition part (i.e. brain) of the robot and develop their own use-cases, all without facing the complexity of integrating different technologies and hardware interfaces.

The future ahead

With latest AI results being translated to robotics, and recent investments in the field, there’s a high anticipation for the near future of robotics.

As nicely introduced by Melonee Wise in a recent interview, there’s still not that many things you can do with a $1000-5000 BOM robot (which is what most people would pay on an individual basis for a robot). Hardware is still a limiting factor, and our team strongly believes that a common infrastructure, such as H-ROS, will facilitate an environment where robot hardware and software can evolve.

The list presented below summarizes, according to our judgement, some of the most technically feasible future robotic technologies to appear.

Acknowledgments

This review was funded and supported by Acutronic Robotics, a firm focused on the development of next-generation robot solutions for a range of clients.

The authors would also like to thank the Erle Robotics and the Acutronic groups for their support and help.

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I’m delighted to announce a new game-changing standard for building robot hardware components: H-ROS (the Hardware Robot Operating System). H-ROS provides manufacturers tools for building interoperable robot components that can easily be exchanged or replaced between robots. H-ROS is about supporting a common environment of robot hardware components, where manufacturers comply with standard interfaces built upon the popular Robot Operating System (ROS).

Powered by ROS and built with industry and developers in mind, H-ROS classifies robot components in 5 types: sensing — used to perceive the world; actuation — allowing interaction with the environment; communication — providing a means of interconnection; cognition — the brain of the robot and hybrid; and the components that group together different sub-components under a common interface. These building-block-style parts come as reusable and reconfigurable components, allowing developers to easily upgrade their robots with hardware from different manufacturers, and add new features in seconds.

Motivation and origin:

Building a robot is tricky. Therefore, it makes sense to reuse existing work in an effort to reduce complexity. Unfortunately, nowadays there are few projects, either in industry or academy, that reuse hardware. Robots are generally built by multidisciplinary teams (generally a whole research group or company division), and different engineers get involved in the mechanical, electrical and logical design. Most of the time is spent dealing with the hardware/software interfaces, and little effort is put into behavior development or real-world scenarios.

Existing hardware platforms—although becoming more common—lack extensibility. Examples can be seen in several commercial and industrial robots that hit the market recently, and already include a common software infrastructure (generally the Robot Operating System(ROS)) but lack of a hardware standard.

With H-ROS, building robots will be about placing H-ROS-compatible hardware components together to build new robot configurations. Constructing robots will no longer be restricted to a small elite with high technical skills. It will be extended to the wider majority with a general understanding of the sensing and actuation needed for a particular scenario.

H-ROS was initially funded by the US Defense Advanced Research Projects Agency (DARPA) through the Robotics Fast Track program in 2016 and developed by Erle Robotics.

H-ROS was showcased and presented officially at ROSCon 2016 (October 8th-9th) in Seoul, South Korea, and is now available for selected industry partners and will soon be released for the wider robotics community.

Click here for the official H-ROS website

Erle-Spider is a drone with legs powered by Canonical’s new distribution for robots and IoT devices: Snappy Ubuntu Core. This computer with legs uses the Robot Operating System (ROS), and has been unleashed by Erle Robotics, a spanish startup focused on creating artificial brains for robots and drones. Now crowdfunding on Indiegogo, the Spider is powered by a 900MHz quad-core ARM Cortex-A7 microprocessor that includes 1GB of RAM and exposes several connection interfaces including Ethernet, USB, I2C, UART and HDMI. It also includes several sensors such as gyroscopes, a digital compass, a pressure sensor, gravity sensors or temperature sensors and can be further extended with any sensor that is already supported by ROS.

The robot has been created to meet the increasing demand for low cost robot and drone platforms that help in the process of learning, research and development of new ideas. The spider is subject to low levels of regulation when compared to other drones and will provide support for existing tools already adopted by the Dronecode Foundation. Erle Robotics has announced that the Spider will be opened (both in hardware and software once the campaign is successfully funded).

“We’ve always believed that the future of robotics wouldn’t be about humanoids costing thousands of euros, but about Linux-based, open and affordable robots that allow people to put their creativity into real applications. With Erle-Spider using Ubuntu, millions of developers will have access to a robot that can be programmed using the same tools that they use everyday” – Víctor Mayoral Vilches, CTO at Erle Robotics.

Erle-Spider’s capabilities can be extended using “apps”. Developers can easily create these applications for the drone and sell them through the cloud-based app store. The apps can be as simple as a line follower algorithm or as complicated as a behavior that using SLAM helps the spider explore pipes and provide measurements. Creating these applications for the robot doesn’t require any developer licenses (when compared to existing cloud marketplaces for smartphones) and it’s as simple creating a zip file. Furthermore, ROS is integrated within the store thereby it can be used to develop these applications.

“Erle-Spider has literally been designed to explore terrain that other robots and drones haven’t seen yet.” – Alejandro Hernández Cordero, CRO at Erle Robotics.

Erle-Spider will be delivered this Christmas and is available on Indiegogo for 399$ .