Driverless car merging into traffic. How big of a gap between vehicles is acceptable? Image credit: Jordan Collver

I’m examining the perception of autonomous cars using hypothetical scenarios. Each of the hypothetical scenarios is accompanied with an image to help illustrate the scene — using grey tones and nondescript human-like features — along with the option to listen to the question spoken out loud to fully visualise an association. 

If you live in the UK, you can take this survey and help contribute to my research!

Public perception has the potential to impact on the timescale and adoption of autonomous vehicles (AV). As the development of the technology advances, understanding attitudes and wider public acceptability is critical. It’s no longer a question of if, but when we will transition. Long range autonomous vehicles are expected between 2020 and 2025, with some estimates suggesting fully autonomous vehicles will take over by 2030. Currently, most modern cars are sold with automated features: automatic braking, autonomous parking, advanced lane assist, advanced cruise control, queue assist, for example. Adopting fully AV has the potential to improve significant societal aspects: efficient road safety, reducing pollution and congestion, and providing another type of transportation for the mobility impaired.

The project’s aim is to add to the conversation about public perception of AV. Survey experiments can be extremely useful tools for studying public attitudes, especially if researchers are fascinated by the “effects of describing or presenting a scenario in a particular way.”  This unusual and creative method may provide a model for other types of research surveys in the future where it’s difficult to visualise future technologies. An online survey was chosen to remove small sample bias and maximise responses by participants in the UK.

You can take this survey by clicking above, or alternatively, click the following link:

https://uwe.onlinesurveys.ac.uk/visualise-this

Humanoid robots under development can be programmed to detect changes in an elderly person’s preferences and habits. Image credit: GrowMeUp

by Helen Massy-Beresford

Low birth rates and higher life expectancies mean that those over 65 years old now will account for 28.7 % of Europe’s population by 2080, according to Eurostat, the EU’s statistics arm.

It means the age-dependency ratio – the proportion of the elderly compared with the number of workers – will almost double from 28.8 % in 2015 to 51 % in 2080, straining healthcare systems and national budgets.

Yet there’s hope marching over the horizon, in the form of robots.

The creators of one humanoid robot under development for the elderly say it can understand people’s actions and learn new behaviours in response, even though it is devoid of arms.

Robots can be programmed to understand an elderly person’s preferences and habits to detect changes in behaviour: for example if a yoga devotee misses a class, it will ask why, while if an elderly person falls it will automatically alert caregivers or emergency services.

Yet there’s still a way to go before these devices will be able to bring out a tray of tea and biscuits when visitors drop by, according to its creator.

At the moment there are things the robot can perform perfectly in the lab but that still present challenges, says Dr Luís Santos from the University of Coimbra in Portugal, who has been developing the technology as part of an EU-funded research project known as GrowMeUp.

The proportion of elderly people is expected to almost double by 2080, so researchers are looking to robots to see if they can help care for the aging population. Image credit: GrowMeUp

‘There is a mismatch between what elderly people want and what science and technology can provide – some of them are expecting robots to do all types of household activities, engage them in everyday gossip or physically interact with them as another human would do,’ says Dr Santos.

The team is working on making the robot’s dialogue as natural and as intuitive as possible and improving its ability to safely navigate an older person’s home, using a low-cost laser and a camera, and a second prototype will be tested with elderly people in the coming months. Yet, Dr Santos foresees that these devices are still four to six years away from commercialisation, at least.

Revolution

He sees robotics as just a part of a wider revolution underway in how societies care for the elderly, with connectivity and augmented reality also playing a role.

‘In the future, elderly care will also be very focused on information and communications technologies – for example virtual access to doctors or care institutions and 24/7 monitoring in a non-invasive way are likely to become standard,’ he said.

Yet researchers believe that keeping the technology unobtrusive is key – no wearable devices or cumbersome cameras cluttering up people’s homes.

Dr Maria Dagioglou from the National Centre of Scientific Research ‘Demokritos’ in Greece, said: ‘We wanted to avoid a Big Brother scenario, so data privacy is important but also dignity.’

She is looking at ways to integrate robotics technology into a smart home equipped with connected devices, automation and sensors, as part of the EU-funded RADIO project.

Researchers are figuring out ways of putting robots in homes for virtual access to healthcare and constant monitoring, yet that are also non-invasive. Image credit: RADIO

Dr Stasinos Konstantopoulos, the scientific manager of the RADIO project, added: ‘All monitoring happens as the user interacts with the system to control the house, for example, to regulate the temperature, and to ask the robot to run errands, like finding misplaced items.’

Using a tablet or smartphone to interact, the equipment, which should only take a day to install, can monitor elements of an elderly person’s day-to-day life, efficiently processing and managing data to allow medical professionals to keep track of and assess their level of independence via smartphone notifications.

‘It’s a constant safety net in case something starts to be worrying,’ said Dr Dagioglou.

The goal of innovations like this is to allow people to live independently for longer.

A crucial element of this is finding ways for older people to keep up their activity levels, and this is an area where robots could really come into their own.

Dr Luigi Palopoli at the University of Trento in Italy said ‘our robot pushes them to do their exercise, to go out and about; it extracts information on their interests and on their fears and makes them part of a network.’

Barriers

‘We want to tear down the emotional barriers that make them stay at home and degrade the quality of their life,’ he said.

As part of the EU-funded Acanto project, he is developing a robot called FriWalk, following on from the progress made during a previous EU-funded project, the DALi project.

The team has worked hard to make the FriWalk robot look energetic and appealing and to ensure it offers useful services like carrying small items or giving directions.

With prototypes made, in the next few months, the researchers will start clinical trials in Spain as well as public demonstrations of the FriWalk in museums and other public spaces.

Researchers will start clinical trials in Spain of a robotic prototype designed to help elderly people to exercise. Image credit: Acanto

Further ahead, Dr Palopoli hopes for interest from established manufacturers and start-ups to bring the FriWalk technology to the market.

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

•  Choreographing automated cars could save time, money and lives
• 3D-printed houses and cars on the horizon as manufacturing goes large
• Keeping a robotic eye on pollution
• Grow a house with plant-robot hybrids

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

The Jungle Hawk Owl team. Photo: Sally Chapman/MIT

In the event of a natural disaster that disrupts phone and Internet systems over a wide area, autonomous aircraft could potentially hover over affected regions, carrying communications payloads that provide temporary telecommunications coverage to those in need.

However, such unpiloted aerial vehicles, or UAVs, are often expensive to operate, and can only remain in the air for a day or two, as is the case with most autonomous surveillance aircraft operated by the U.S. Air Force. Providing adequate and persistent coverage would require a relay of multiple aircraft, landing and refueling around the clock, with operational costs of thousands of dollars per hour, per vehicle.

Now a team of MIT engineers has come up with a much less expensive UAV design that can hover for longer durations to provide wide-ranging communications support. The researchers designed, built, and tested a UAV resembling a thin glider with a 24-foot wingspan. The vehicle can carry 10 to 20 pounds of communications equipment while flying at an altitude of 15,000 feet. Weighing in at just under 150 pounds, the vehicle is powered by a 5-horsepower gasoline engine and can keep itself aloft for more than five days — longer than any gasoline-powered autonomous aircraft has remained in flight, the researchers say.

The team is presenting its results this week at the American Institute of Aeronautics and Astronautics Conference in Denver, Colorado. The team was led by R. John Hansman, the T. Wilson Professor of Aeronautics and Astronautics; and Warren Hoburg, the Boeing Assistant Professor of Aeronautics and Astronautics. Hansman and Hoburg are co-instructors for MIT’s Beaver Works project, a student research collaboration between MIT and the MIT Lincoln Laboratory.

A solar no-go

Hansman and Hoburg worked with MIT students to design a long-duration UAV as part of a Beaver Works capstone project — typically a two- or three-semester course that allows MIT students to design a vehicle that meets certain mission specifications, and to build and test their design.

In the spring of 2016, the U.S. Air Force approached the Beaver Works collaboration with an idea for designing a long-duration UAV powered by solar energy. The thought at the time was that an aircraft, fueled by the sun, could potentially remain in flight indefinitely. Others, including Google, have experimented with this concept,  designing solar-powered, high-altitude aircraft to deliver continuous internet access to rural and remote parts of Africa.

But when the team looked into the idea and analyzed the problem from multiple engineering angles, they found that solar power — at least for long-duration emergency response — was not the way to go.

“[A solar vehicle] would work fine in the summer season, but in winter, particularly if you’re far from the equator, nights are longer, and there’s not as much sunlight  during the day. So you have to carry more batteries, which adds weight and makes the plane bigger,” Hansman says. “For the mission of disaster relief, this could only respond to disasters that occur in summer, at low latitude. That just doesn’t work.”

The researchers came to their conclusions after modeling the problem using GPkit, a software tool developed by Hoburg that allows engineers to determine the optimal design decisions or dimensions for a vehicle, given certain constraints or mission requirements.

This method is not unique among initial aircraft design tools, but unlike these tools, which take into account only several main constraints, Hoburg’s method allowed the team to consider around 200 constraints and physical models simultaneously, and to fit them all together to create an optimal aircraft design.

“This gives you all the information you need to draw up the airplane,” Hansman says. “It also says that for every one of these hundreds of parameters, if you changed one of them, how much would that influence the plane’s performance? If you change the engine a bit, it will make a big difference. And if you change wingspan, will it show an effect?”

Framing for takeoff

After determining, through their software estimations, that a solar-powered UAV would not be feasible, at least for long-duration use in any part of the world, the team performed the same modeling for a gasoline-powered aircraft. They came up with a design that was predicted to stay in flight for more than five days, at altitudes of 15,000 feet, in up to 94th-percentile winds, at any latitude.

In the fall of 2016, the team built a prototype UAV, following the dimensions determined by students using Hoburg’s software tool. To keep the vehicle lightweight, they used materials such as carbon fiber for its wings and fuselage, and Kevlar for the tail and nosecone, which houses the payload. The researchers designed the UAV to be easily taken apart and stored in a FedEx box, to be shipped to any disaster region and quickly reassembled.

This spring, the students refined the prototype and developed a launch system, fashioning a simple metal frame to fit on a typical car roof rack. The UAV sits atop the frame as a driver accelerates the launch vehicle (a car or truck) up to rotation speed — the UAV’s optimal takeoff speed. At that point, the remote pilot would angle the UAV toward the sky, automatically releasing a fastener and allowing the UAV to lift off.

In early May, the team put the UAV to the test, conducting flight tests at Plum Island Airport in Newburyport, Massachusetts. For initial flight testing, the students modified the vehicle to comply with FAA regulations for small unpiloted aircraft, which allow drones flying at low altitude and weighing less than 55 pounds. To reduce the UAV’s weight from 150 to under 55 pounds, the researchers simply loaded it with a smaller ballast payload and less gasoline.

In their initial tests, the UAV successfully took off, flew around, and landed safely. Hoburg says there are special considerations that have to be made to test the vehicle over multiple days, such as having enough people to monitor the aircraft over a long period of time.

“There are a few aspects to flying for five straight days,” Hoburg says. “But we’re pretty confident that we have the right fuel burn rate and right engine that we could fly it for five days.”

“These vehicles could be used not only for disaster relief but also other missions, such as environmental monitoring. You might want to keep watch on wildfires or the outflow of a river,” Hansman adds. “I think it’s pretty clear that someone within a few years will manufacture a vehicle that will be a knockoff of this.”

This research was supported, in part, by MIT Lincoln Laboratory.

A GelSight sensor attached to a robot’s gripper enables the robot to determine precisely where it has grasped a small screwdriver, removing it from and inserting it back into a slot, even when the gripper screens the screwdriver from the robot’s camera. Photo: Robot Locomotion Group at MIT

Eight years ago, Ted Adelson’s research group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) unveiled a new sensor technology, called GelSight, that uses physical contact with an object to provide a remarkably detailed 3-D map of its surface.

Now, by mounting GelSight sensors on the grippers of robotic arms, two MIT teams have given robots greater sensitivity and dexterity. The researchers presented their work in two papers at the International Conference on Robotics and Automation last week.

In one paper, Adelson’s group uses the data from the GelSight sensor to enable a robot to judge the hardness of surfaces it touches — a crucial ability if household robots are to handle everyday objects.

In the other, Russ Tedrake’s Robot Locomotion Group at CSAIL uses GelSight sensors to enable a robot to manipulate smaller objects than was previously possible.

The GelSight sensor is, in some ways, a low-tech solution to a difficult problem. It consists of a block of transparent rubber — the “gel” of its name — one face of which is coated with metallic paint. When the paint-coated face is pressed against an object, it conforms to the object’s shape.

The metallic paint makes the object’s surface reflective, so its geometry becomes much easier for computer vision algorithms to infer. Mounted on the sensor opposite the paint-coated face of the rubber block are three colored lights and a single camera.

“[The system] has colored lights at different angles, and then it has this reflective material, and by looking at the colors, the computer … can figure out the 3-D shape of what that thing is,” explains Adelson, the John and Dorothy Wilson Professor of Vision Science in the Department of Brain and Cognitive Sciences.

In both sets of experiments, a GelSight sensor was mounted on one side of a robotic gripper, a device somewhat like the head of a pincer, but with flat gripping surfaces rather than pointed tips.

Contact points

For an autonomous robot, gauging objects’ softness or hardness is essential to deciding not only where and how hard to grasp them but how they will behave when moved, stacked, or laid on different surfaces. Tactile sensing could also aid robots in distinguishing objects that look similar.

In previous work, robots have attempted to assess objects’ hardness by laying them on a flat surface and gently poking them to see how much they give. But this is not the chief way in which humans gauge hardness. Rather, our judgments seem to be based on the degree to which the contact area between the object and our fingers changes as we press on it. Softer objects tend to flatten more, increasing the contact area.

The MIT researchers adopted the same approach. Wenzhen Yuan, a graduate student in mechanical engineering and first author on the paper from Adelson’s group, used confectionary molds to create 400 groups of silicone objects, with 16 objects per group. In each group, the objects had the same shapes but different degrees of hardness, which Yuan measured using a standard industrial scale.

Then she pressed a GelSight sensor against each object manually and recorded how the contact pattern changed over time, essentially producing a short movie for each object. To both standardize the data format and keep the size of the data manageable, she extracted five frames from each movie, evenly spaced in time, which described the deformation of the object that was pressed.

Finally, she fed the data to a neural network, which automatically looked for correlations between changes in contact patterns and hardness measurements. The resulting system takes frames of video as inputs and produces hardness scores with very high accuracy. Yuan also conducted a series of informal experiments in which human subjects palpated fruits and vegetables and ranked them according to hardness. In every instance, the GelSight-equipped robot arrived at the same rankings.

Yuan is joined on the paper by her two thesis advisors, Adelson and Mandayam Srinivasan, a senior research scientist in the Department of Mechanical Engineering; Chenzhuo Zhu, an undergraduate from Tsinghua University who visited Adelson’s group last summer; and Andrew Owens, who did his PhD in electrical engineering and computer science at MIT and is now a postdoc at the University of California at Berkeley.

Obstructed views

The paper from the Robot Locomotion Group was born of the group’s experience with the Defense Advanced Research Projects Agency’s Robotics Challenge (DRC), in which academic and industry teams competed to develop control systems that would guide a humanoid robot through a series of tasks related to a hypothetical emergency.

Typically, an autonomous robot will use some kind of computer vision system to guide its manipulation of objects in its environment. Such systems can provide very reliable information about an object’s location — until the robot picks the object up. Especially if the object is small, much of it will be occluded by the robot’s gripper, making location estimation much harder. Thus, at exactly the point at which the robot needs to know the object’s location precisely, its estimate becomes unreliable. This was the problem the MIT team faced during the DRC, when their robot had to pick up and turn on a power drill.

“You can see in our video for the DRC that we spend two or three minutes turning on the drill,” says Greg Izatt, a graduate student in electrical engineering and computer science and first author on the new paper. “It would be so much nicer if we had a live-updating, accurate estimate of where that drill was and where our hands were relative to it.”

That’s why the Robot Locomotion Group turned to GelSight. Izatt and his co-authors — Tedrake, the Toyota Professor of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering; Adelson; and Geronimo Mirano, another graduate student in Tedrake’s group — designed control algorithms that use a computer vision system to guide the robot’s gripper toward a tool and then turn location estimation over to a GelSight sensor once the robot has the tool in hand.

In general, the challenge with such an approach is reconciling the data produced by a vision system with data produced by a tactile sensor. But GelSight is itself camera-based, so its data output is much easier to integrate with visual data than the data from other tactile sensors.

In Izatt’s experiments, a robot with a GelSight-equipped gripper had to grasp a small screwdriver, remove it from a holster, and return it. Of course, the data from the GelSight sensor don’t describe the whole screwdriver, just a small patch of it. But Izatt found that, as long as the vision system’s estimate of the screwdriver’s initial position was accurate to within a few centimeters, his algorithms could deduce which part of the screwdriver the GelSight sensor was touching and thus determine the screwdriver’s position in the robot’s hand.

“I think that the GelSight technology, as well as other high-bandwidth tactile sensors, will make a big impact in robotics,” says Sergey Levine, an assistant professor of electrical engineering and computer science at the University of California at Berkeley. “For humans, our sense of touch is one of the key enabling factors for our amazing manual dexterity. Current robots lack this type of dexterity and are limited in their ability to react to surface features when manipulating objects. If you imagine fumbling for a light switch in the dark, extracting an object from your pocket, or any of the other numerous things that you can do without even thinking — these all rely on touch sensing.”

“Software is finally catching up with the capabilities of our sensors,” Levine adds. “Machine learning algorithms inspired by innovations in deep learning and computer vision can process the rich sensory data from sensors such as the GelSight to deduce object properties. In the future, we will see these kinds of learning methods incorporated into end-to-end trained manipulation skills, which will make our robots more dexterous and capable, and maybe help us understand something about our own sense of touch and motor control.”

Engineers at MIT have come up with an algorithm to tune a Dynamic Vision Sensor (DVS) camera, simplifying a scene to its most essential visual elements and potentially enabling the development of faster drones. Image: Jose-Luis Olivares/MIT

There’s a limit to how fast autonomous vehicles can fly while safely avoiding obstacles. That’s because the cameras used on today’s drones can only process images so fast, frame by individual frame. Beyond roughly 30 miles per hour, a drone is likely to crash simply because its cameras can’t keep up.

Recently, researchers in Zurich invented a new type of camera, known as the Dynamic Vision Sensor (DVS), that continuously visualizes a scene in terms of changes in brightness, at extremely short, microsecond intervals. But this deluge of data can overwhelm a system, making it difficult for a drone to distinguish an oncoming obstacle through the noise.

Now engineers at MIT have come up with an algorithm to tune a DVS camera to detect only specific changes in brightness that matter for a particular system, vastly simplifying a scene to its most essential visual elements.

The results, which they presented at the IEEE American Control Conference in Seattle, can be applied to any linear system that directs a robot to move from point A to point B as a response to high-speed visual data. Eventually, the results could also help to increase the speeds for more complex systems such as drones and other autonomous robots.

“There is a new family of vision sensors that has the capacity to bring high-speed autonomous flight to reality, but researchers have not developed algorithms that are suitable to process the output data,” says lead author Prince Singh, a graduate student in MIT’s Department of Aeronautics and Astronautics. “We present a first approach for making sense of the DVS’ ambiguous data, by reformulating the inherently noisy system into an amenable form.”

Singh’s co-authors are MIT visiting professor Emilio Frazzoli of the Swiss Federal Institute of Technology in Zurich, and Sze Zheng Yong of Arizona State University.

Taking a visual cue from biology

The DVS camera is the first commercially available “neuromorphic” sensor — a class of sensors that is modeled after the vision systems in animals and humans. In the very early stages of processing a scene, photosensitive cells in the human retina, for example, are activated in response to changes in luminosity, in real time.

Neuromorphic sensors are designed with multiple circuits arranged in parallel, similarly to photosensitive cells, that activate and produce blue or red pixels on a computer screen in response to either a drop or spike in brightness.

Instead of a typical video feed, a drone with a DVS camera would “see” a grainy depiction of pixels that switch between two colors, depending on whether that point in space has brightened or darkened at any given moment. The sensor requires no image processing and is designed to enable, among other applications, high-speed autonomous flight.

Researchers have used DVS cameras to enable simple linear systems to see and react to high-speed events, and they have designed controllers, or algorithms, to quickly translate DVS data and carry out appropriate responses. For example, engineers have designed controllers that interpret pixel changes in order to control the movements of a robotic goalie to block an incoming soccer ball, as well as to direct a motorized platform to keep a pencil standing upright.

But for any given DVS system, researchers have had to start from scratch in designing a controller to translate DVS data in a meaningful way for that particular system.

“The pencil and goalie examples are very geometrically constrained, meaning if you give me those specific scenarios, I can design a controller,” Singh says. “But the question becomes, what if I want to do something more complicated?”

Cutting through the noise

In the team’s new paper, the researchers report developing a sort of universal controller that can translate DVS data in a meaningful way for any simple linear, robotic system. The key to the controller is that it identifies the ideal value for a parameter Singh calls “H,” or the event-threshold value, signifying the minimum change in brightness that the system can detect.

Setting the H value for a particular system can essentially determine that system’s visual sensitivity: A system with a low H value would be programmed to take in and interpret changes in luminosity that range from very small to relatively large, while a high H value would exclude small changes, and only “see” and react to large variations in brightness.

The researchers formulated an algorithm first by taking into account the possibility that a change in brightness would occur for every “event,” or pixel activated in a particular system. They also estimated the probability for “spurious events,” such as a pixel randomly misfiring, creating false noise in the data.

Once they derived a formula with these variables in mind, they were able to work it into a well-known algorithm known as an H-infinity robust controller, to determine the H value for that system.

The team’s algorithm can now be used to set a DVS camera’s sensitivity to detect the most essential changes in brightness for any given linear system, while excluding extraneous signals. The researchers performed a numerical simulation to test the algorithm, identifying an H value for a theoretical linear system, which they found was able to remain stable and carry out its function without being disrupted by extraneous pixel events.

“We found that this H threshold serves as a ‘sweet-spot,’ so that a system doesn’t become overwhelmed with too many events,” Singh says. He adds that the new results “unify control of many systems,” and represent a first step toward faster, more stable autonomous flying robots, such as the Robobee, developed by researchers at Harvard University.

“We want to break that speed limit of 20 to 30 miles per hour, and go faster without colliding,” Singh says. “The next step may be to combine DVS with a regular camera, which can tell you, based on the DVS rendering, that an object is a couch versus a car, in real time.”

This research was supported in part by the Singapore National Research Foundation through the SMART Future Urban Mobility project.

Latvian drone manufacturer Aerones organized the world’s first drone skydive. Credit: Aerones/YouTube

News

A U.S. Court of Appeals has struck down the Federal Aviation Administration’s drone registration requirement for recreational operators. The federal court ruled that the registration system violates the 2012 FAA Modernization and Reform Act, which does not grant the FAA the authority to regulate hobby aircraft. More than 820,000 people have registered their drones with the FAA since the requirement was implemented in 2015. (Recode)

Commentary, Analysis, and Art

At the Harvard Business Review, Chris Anderson examines the economic potential of drones to transform industries like construction.

At Wired, Rhett Allain studies the physics of a quadcopter in flight.

In a statement, Senator John Hoeven (R-ND) urges the Department of Defense to develop an air traffic management system for drones. (Press Release)

In a speech at the Special Operations Forces Industry Conference, General Raymond Thomas said that armed ISIS drones were the “most daunting problem” of the past year. (DefenseNews)

The U.S. Appropriations Subcommittee on Transportation, Housing and Urban Development held a hearing on drones and self-driving cars.

At the Indianapolis Star, Ryan Martin writes that police departments in Indiana are pushing back against a state law that prohibits police from using drones for surveillance.

At War is Boring, David Axe looks at how the U.S. Air Force is using robotic F-16 fighters to test the teaming of manned and unmanned aircraft in combat.

At The Strategy Bridge, Brian M. Michelson considers the challenge of accountability in autonomous weapons.

At the Intercept, Shuaib Almosawa and Murtaza Hussain write that family members of individuals killed in a U.S. drone strike are disputing claims that the men were members of al-Qaeda.

At Vox, Timothy B. Lee writes that artificial intelligence is “getting more powerful, and it’s about to be everywhere.”

At Popular Science, Kelsey D. Atherton looks at how ISIS is developing remote-controlled weapons that appear similar to some of the earliest drones.

At Ars Technica, Megan Geuss visits a drone racing event to discover the appeal that draws would-be racers to the budding sport.

The Digital Forensic Research Lab look at how separatists in Ukraine use drones and text messages to spread propaganda.

Paint By Drone, a graffiti drone system, will create its first two installations in Berlin and Turin later this year. (Progrss)

Know Your Drone

Amazon announced that is has started development of an air traffic management system for its delivery drones. (Bloomberg)

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and ETH Zurich in Switzerland are developing systems that enable drones to maintain the exact framing of a scene specified by the operator. (Engadget)

The U.S. Naval Research Laboratory is working to develop solar-powered unmanned aircraft that can remain aloft for extended periods. (R&D Magazine)

Maritime firms Yara and Kongsberg are partnering to develop an autonomous electric cargo ship that produces zero emissions. (Unmanned Systems Technology)

An official at the U.S. Army’s Tank Automotive Research, Development and Engineering Center has said that the service’s next tank will have the ability to operate aerial drones. (War is Boring)

In a test, a robotic co-pilot system developed by Aurora Flight Sciences successfully landed a simulated Boeing 737 commercial airliner. (Aviation Week)  

Researchers at the Georgia Institute of Technology are developing drone swarms in which the aircraft are protected by a virtual bumper area that prevents them from crashing into each other. (Engadget)

The Air Force Research Laboratory released a rendering of what appears to be its planned Low Cost Attritable Aircraft Technology drone. (The Drive)

Meanwhile, the Air Force Research Laboratory presented a number of unmanned aircraft projects at the second biennial Department of Defense Lab Day, including the Ninja counter-drone system and the Low Cost Attritable Aircraft Technology Program. (Press Release)

U.S. firm Endeavor Robotics unveiled a variant of its 710 Kobra ground robot armed with a 7.62mm machine gun. (Shephard Media)

The Unmanned Mine Counter Measure Integrated System, an unmanned undersea vessel built by Russian shipyard SNSZ, has been declared fully operational with the Kazakh Navy. (Press Release)

Singapore-based firm Zycraft announced that its Independent USV completed a test in which it was deployed in the South China Sea for a continuous period of 22 days. (IHS Jane’s 360)

The U.S. Air Force Research Laboratory is developing small unmanned aircraft that can be launched from AC-130 gunships or similar manned aircraft. (IHS Jane’s 360)

During a trial operation off the coast of San Clemente Island, a U.S. Navy MQ-8B Fire Scout  drone helicopter served as a laser designation platform for a Hellfire missile fired from an MH-60S Knighthawk helicopter. (Press Release)

Drones at Work

Japanese fighter jets were scrambled in response to a drone operated by a Chinese vessel over disputed waters in the East China Sea. (Nikkei Asian Review)

A Jordanian Air Force F-16 fighter jet shot down a drone that was flying near the Syrian border.  (IHS Jane’s 360)

Police in South Pasadena, California used a drone to aid in the search for a missing boy. (The Los Angeles Times)  

Officials in Elk City, Oklahoma enlisted students from Embry-Riddle Aeronautical University to survey damage from a recent tornado with a drone. (News9)

Two aerial inspection services companies, AirShark and Unmanned Experts, used drones to inspect a crucial railroad bridge in New York State. (Unmanned Aerial Online)

The West Australia Police air wing is planning to test drones for a range of operations including investigations and search and rescue missions. (The West Australian)

Researchers using drones to study narwhals found that the animals appear to use use their long, sharp tusks to stun their prey. (New Atlas)

U.S. startup DroneSeed has obtained FAA approval to operate multiple drones carrying agricultural payloads. (Unmanned Aerial Online)

Police in Brick Township, New Jersey have purchased a drone for search and rescue and scene documentation. (App.com)

As part of an inauguration ceremony for an unmanned aircraft runway, Virginia governor Terry McAuliffe flew in a remotely piloted airplane. (Press Release)

Researchers at the University of California are using drones to study tortoise habitats in the Mojave Desert. (IGIS)

The Les Nicolles prison in the the U.K. has installed a Sky Fence counter-drone system. (The Telegraph)

The Israeli Air Force is planning to replace its Sea Scan manned maritime patrol aircraft with the IAI Heron 1, a medium-altitude long-endurance drone. (UPI)  

Industry Intel

DroneWERX, a new initiative by the U.S. Special Operations Command and Strategic Capabilities Office, will focus on rapidly acquiring and fielding new drones and robots, swarms, and machine learning and artificial intelligence technologies for special operations. (DefenseNews)

The U.S. Special Operations Command has placed an urgent order for 325 AeroVironment Switchblade loitering munition drones. (Defense One) For more on loitering munitions, click here.

The U.S. Air Force awarded General Atomics Aeronautical Systems a $400 million contract for 36 MQ-9 Reaper aircraft. (DoD)

The U.S. Navy awarded Northrop Grumman Systems a $303.9 million contract modification for three Lot 2 MQ-4C Triton unmanned aircraft and associated equipment. (DoD)

The U.S. Navy awarded Leidos a $299,570 contract for the Open Ocean Counter Unmanned Underwater Vehicle. (FBO)

The Defense Innovation Unit Experimental awarded FlyMotion a $35,388 contract for DJI drones. (FBO)

Delphi will collaborate with BMW, Intel, and Mobileye to develop and field automated vehicles by 2021. (Associated Press)

Silverstone, the British racing circuit, has reportedly contracted Drone Defence to provide counter-drone systems for the Formula 1 race in July. (The Sun)

The University of Aarhus in Denmark awarded YellowScan a $114,316 contract for a UAS LiDAR solution for surveying. (Ted)

Saudi Arabia launched the Saudi Arabian Military Industries, a state-owned military industrial company that will manufacture drones, as well as a variety of other military systems and equipment. (Reuters)

Amazon will open a research center outside of Paris that will focus on developing its Prime Air drone delivery concept. (Venture Beat)

For updates, news, and commentary, follow us on Twitter. The Weekly Drone Roundup is a newsletter from the Center for the Study of the Drone. It covers news, commentary, analysis and technology from the drone world. You can subscribe to the Roundup here.

“The new frontier is learning how to design the relationships between people, robots, and infrastructure,” says David Mindell, the Dibner Professor of the History of Engineering and Manufacturing, and a professor of aeronautics and astronautics. “We need new sensors, new software, new ways of architecting systems.” Photo: Len Rubenstein

Science and technology are essential tools for innovation, and to reap their full potential, we also need to articulate and solve the many aspects of today’s global issues that are rooted in the political, cultural, and economic realities of the human world. With that mission in mind, MIT’s School of Humanities, Arts, and Social Sciences has launched The Human Factor — an ongoing series of stories and interviews that highlight research on the human dimensions of global challenges. Contributors to this series also share ideas for cultivating the multidisciplinary collaborations needed to solve the major civilizational issues of our time.

David Mindell, the Frances and David Dibner Professor of the History of Engineering and Manufacturing and Professor of Aeronautics and Astronautics at MIT, researches the intersections of human behavior, technological innovation, and automation. Mindell is the author of five acclaimed books, most recently “Our Robots, Ourselves: Robotics and the Myths of Autonomy” (Viking, 2015). He is also the co-founder of Humatics Corporation, which develops technologies for human-centered automation. SHASS Communications recently asked him to share his thoughts on the relationship of robotics to human activities, and the role of multidisciplinary research in solving complex global issues.

Q: A major theme in recent political discourse has been the perceived impact of robots and automation on the United States labor economy. In your research into the relationship between human activity and robotics, what insights have you gained that inform the future of human jobs, and the direction of technological innovation?

A: In looking at how people have designed, used, and adopted robotics in extreme environments like the deep ocean, aviation, or space, my most recent work shows how robotics and automation carry with them human assumptions about how work gets done, and how technology alters those assumptions. For example, the U.S. Air Force’s Predator drones were originally envisioned as fully autonomous — able to fly without any human assistance. In the end, these drones require hundreds of people to operate.

The new success of robots will depend on how well they situate into human environments. As in chess, the strongest players are often the combinations of human and machine. I increasingly see that the three critical elements are people, robots, and infrastructure — all interdependent.

Q: In your recent book “Our Robots, Ourselves,” you describe the success of a human-centered robotics, and explain why it is the more promising research direction — rather than research that aims for total robotic autonomy. How is your perspective being received by robotic engineers and other technologists, and do you see examples of research projects that are aiming at human-centered robotics?

A: One still hears researchers describe full autonom as the only way to go; often they overlook the multitude of human intentions built into even the most autonomous systems, and the infrastructure that surrounds them. My work describes situated autonomy, where autonomous systems can be highly functional within human environments such as factories or cities. Autonomy as a means of moving through physical environments has made enormous strides in the past ten years. As a means of moving through human environments, we are only just beginning. The new frontier is learning how to design the relationships between people, robots, and infrastructure. We need new sensors, new software, new ways of architecting systems.

Q: What can the study of the history of technology teach us about the future of robotics?

A: The history of technology does not predict the future, but it does offer rich examples of how people build and interact with technology, and how it evolves over time. Some problems just keep coming up over and over again, in new forms in each generation. When the historian notices such patterns, he can begin to ask: Is there some fundamental phenomenon here? If it is fundamental, how is it likely to appear in the next generation? Might the dynamics be altered in unexpected ways by human or technical innovations?

One such pattern is how autonomous systems have been rendered less autonomous when they make their way into real world human environments. Like the Predator drone, future military robots will likely be linked to human commanders and analysts in some ways as well. Rather than eliding those links, designing them to be as robust and effective as possible is a worthy focus for researchers’ attention.

Q: MIT President L. Rafael Reif has said that the solutions to today’s challenges depend on marrying advanced technical and scientific capabilities with a deep understanding of the world’s political, cultural, and economic realities. What barriers do you see to multidisciplinary, sociotechnical collaborations, and how can we overcome them?

A: I fear that as our technical education and research continues to excel, we are building human perspectives into technologies in ways not visible to our students. All data, for example, is socially inflected, and we are building systems that learn from those data and act in the world. As a colleague from Stanford recently observed, go to Google image search and type in “Grandma” and you’ll see the social bias that can leak into data sets — the top results all appear white and middle class.

Now think of those data sets as bases of decision making for vehicles like cars or trucks, and we become aware of the social and political dimensions that we need to build into systems to serve human needs. For example, should driverless cars adjust their expectations for pedestrian behavior according to the neighborhoods they’re in?

Meanwhile, too much of the humanities has developed islands of specialized discourse that is inaccessible to outsiders. I used to be more optimistic about multidisciplinary collaborations to address these problems. Departments and schools are great for organizing undergraduate majors and graduate education, but the old two-cultures divides remain deeply embedded in the daily practices of how we do our work. I’ve long believed MIT needs a new school to address these synthetic, far-reaching questions and train students to think in entirely new ways.

Interview prepared by MIT SHASS Communications
Editorial team: Emily Hiestand (series editor), Daniel Evans Pritchard

NAO robot. Photo courtesy: Paul Bremner/UWE

I was asked to write a short op-ed on the European Parliament Law Committee’s recommendations on civil law rules for robotics. In the end, the piece didn’t get published, so I am posting it here:

It is a great shame that most reports of the European Parliament’s Committee for Legal Affairs’ vote on its Draft Report on Civil Law Rules on Robotics headlined on ‘personhood’ for robots because the report has much else to commend it. Most important among its several recommendations is a proposed code of ethical conduct for roboticists, which explicitly asks designers to research and innovate responsibly. Some may wonder why such an invitation even needs to be made but, given that engineering and computer science education rarely includes classes on ethics (it should), it is really important that robotics engineers reflect on their ethical responsibilities to society – especially given how disruptive robot technologies are. This is not new – great frameworks for responsible research and innovation already exist. One such is the 2014 Rome Declaration on RRI, and in 2015 the Foundation for Responsible Robotics was launched.

Within the report’s draft Code of Conduct is a call for robotics funding proposals to include a risk assessment. This too is a very good idea and guidance already exists in British Standard BS 8611, published in April 2016. BS 8611 sets out a comprehensive set of ethical risks and offers guidance on how to mitigate them. It is very good also to see that the Code stresses that humans, not robots, are the responsible agents; this is something we regarded as fundamental when we drafted the Principles of Robotics in 2010.

For me, transparency (or the lack of it) is an increasing worry in both robots and AI systems. Labour’s industry spokesperson Chi Onwurah is right to say, “Algorithms are part of our world, so they are subject to regulation, but because they are not transparent, it’s difficult to regulate them effectively” (and don’t forget that it is algorithms that make intelligent robots intelligent). So it is very good to see the draft Code call for robotics engineers to “guarantee transparency … and right of access to information by all stakeholders”, and then in the draft ‘Licence for Designers’: you should ensure “maximal transparency” and even more welcome “you should develop tracing tools that … facilitate accounting and explanation of robotic behaviour… for experts, operators and users”.  Within the IEEE Standards Association Global Initiative on Ethics in AI and Autonomous Systems, launched in 2016, we are working on a new standard on Transparency in Autonomous Systems.

This brings me to standards and regulation.  I am absolutely convinced that regulation, together with transparency and public engagement, builds public trust. Why is it that we trust our tech? Not just because it’s cool and convenient, but also because it’s safe (and we assume that the disgracefully maligned experts will take care of assuring that safety). One of the reasons we trust airliners is that we know they are part of a highly regulated industry with an amazing safety record. The reason commercial aircraft are so safe is not just good design, it is also the tough safety certification processes and, when things do go wrong, robust processes of air accident investigation. So the Report’s call for a European Agency for Robotics and AI to recommend standards and regulatory framework is, as far as I’m concerned, not a moment too soon. We urgently need standards for safety certification of a wide range of robots, from drones and driverless cars to robots for care and assisted living.

Like many of my robotics colleagues, I am deeply worried by the potential for robotics and AI to increase levels of economic inequality in the world. Winnie Byanyima, executive director of Oxfam writes for the WEF, “We need fundamental change to our economic model. Governments must stop hiding behind ideas of market forces and technological change. They … need to steer the direction of technological development”. I think she is right – we need a serious public conversation about technological unemployment and how we ensure that the wealth created by AI and Automonous Systems is shared by all. A Universal Basic Income may or may not be the best way to do this – but it is very encouraging to see this question raised in the draft Report.

I cannot close the piece without at least mentioning artificial personhood. My own view is that personhood is the solution to a problem that doesn’t exist. I can understand why, in the context of liability, the Report raises this question for discussion, but – as the report itself later asserts in the Code of Conduct: humans, not robots, are the responsible agents. Robots are and should remain, artefacts.

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

• Does AI pose a threat to society?
• The infrastructure of life part 1: Safety
• The infrastructure of life part 2: Transparency
• Ethically Aligned Design
• Robust and transparent governance is key to building trust in driverless cars

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

It was the event we have worked towards since the founding of RoboValley: the International Robotics Week. Last week, we were able to show the whole world what RoboValley has built in the past years and what RoboValley stands for: connecting robots and people worldwide.

We would like to thank everyone who contributed to the success of the International Robotics Week: our partners from Robo Business Media, Chrysalix, Accenture, Rabobank, InnovationQuarter, the city of Delft, the Innovation Attaché Network and the speakers and visitors.

Integrating RoboBusiness Europe, TUS Expo and ROS Industrial in one event turned out to be a huge success. For three days, experts in the field of robotics and unmanned systems, and their robots and drones, from all over the world gathered in the Netherlands. The week saw an expo and conference in the World Forum The Hague, tours to labs of the Delft University of Technology and demonstration days in the port of Rotterdam (unmanned harbour) and former airport Valkenburg (drone show). This made clear that the Netherlands has everything needed for robotics companies that want to settle here.

Keynotes
The International Robotics week started on Wednesday, with inspiring keynotes from Kim Liebregts (Tesla Benelux), Noel Sharkey (Responsible Robotics) and Melonee Wise (Fetch Robotics). Wise’s contribution was of particular interest. She pointed out that there are around 1000 robotics start-ups in the world, most of these founded after 2010. Why is that? The answer is open-source robotics (ROS). “Why did this sudden explosion happen? Because of open innovation.” Her company also benefited from ROS.

Sharkey told visitors to think about the ethical aspects of robotics. “We don’t want to sleepwalk into robotics just as we did with the internet.”

Business wise
The IRW is the perfect place for start-ups to present themselves. Prince Constantijn, the start-up envoy of StartupDelta, had some advice for them. The preconditions for being successful in the Netherlands are present, but it is not enough to just have a good product. To give this product a place in the market, you have to be ‘business wise’: you need to surround yourself with people who have a sense of enterprise.

Constantijn also visited the RoboValley pavilion, where various start-ups were gathered together: Delft Robotics, CropZoomer, Clear Flight Solutions, SeaDrone, Robot Care Systems, Robot Security Systems, Robot Engineered Systems, Vectioneer. Also present were the student DreamTeam: Project MARCH, ImProvia and the Care-o-bot from Fraunhofer / Unity Robotics. During the start-up event, AeroVinci announced they received a subsidy of 300 thousand euros. This allows them to further develop the dronedock technology.

Portal: connect.robovalley.com
During the IRW, we also launched the beta version of connect.robovalley.com: ‘your compass in the world of robotics’. Connect.robovalley.com offers a single place for companies to find the latest news, insights and reports on robotics.

RoboValley Foundation Dinner
Networking is an important part of a large congress. Because of this, we were happy that the city of Delft and InnovationQuarter enabled us to host the first RoboCafé NL in the old town hall of the city of Delft on the first evening of the event. Futurist Aseem Prakash delivered an inspiring presentation, the historical ambience took care of the rest.

A day later, we organised the RoboValley Foundation Dinner in our own offices. The Dutch robotics sector was present, as were several international guests. They were, amongst others, addressed by Delft University of Technology’s rector magnificus Karel Luyben, Aimee van Wynsberghe and Guszti Eiben.

‘Golden Age of Nerds’
“We are living in a golden age of nerds”, concluded comedian Pep Rosenfeld during the closing keynotes a day later. He is right. During the IRW, it became clear how much is happening in the field of robotics and how fast developments are moving. “Robotics and AI are all about possibilities”, said Prakash during his keynote. “Possibilities that humans never have experienced before.”

There was room for ethical issues during the closing keynotes. Irakli Beridze of the United Nations Interregional Crime and Justice Research Institute told us what the UN is doing in the fields of robotics and AI. Beridze and his organisation have settled in The Hague because of the presence of the Responsible Robotics Foundation. “By joining forces, we want to make this a city of ideas and global policies related to AI and robotics.”

“Over the past few years, we have built a global platform for organisations and people involved in robotics”

RoboValley Platform
RoboValley’s Managing Director, Arthur de Crook, thanked everyone at the end of the IRW. He explained the importance of the event for RoboValley. “Over the past few years, we have built a global platform for organisations, researchers and governments involved in robotics. But we also really wanted to create a moment to show this platform to the world. This moment was the International Robotics Week.” Robotics can contribute to solving the grand societal challenges. This is why it is important to create the next generation robotics. “So we can embrace the future for the good.”

Credit: Crash Course/YouTube

Crash Course is a video channel you can access through YouTube. Crash Course Computer Science is an ongoing playlist of fast-moving videos that begin with the most basic underpinnings of digital computing and progress from there.

If you are a complete novice, you’ll probably want to take them one at a time, watch each several times, and perhaps also supplement them with other sources, to make sure you understand each new concept.

If you’re already somewhat familiar with the subject, this is a great review!

MIT Professor Daniela Rus, director of CSAIL, said the goal of a new SystemsThatLearn@CSAIL initiative is “to create a new generation of AI tools that are deeply rooted in systems.” Photo: Jason Dorfman/MIT CSAIL

From self-driving cars to the internet of things, artificial intelligence (AI) has reached new levels of sophistication in recent years. With that in mind, this week MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) launched an industry collaboration focused on using machine learning to create functional human-like systems.

Nearly 40 senior researchers will participate in the new “SystemsThatLearn@CSAIL” (STL) initiative alongside a range of organizations that include founding members BT, Microsoft, Nokia Bell Labs, Salesforce, and Schlumberger. Member companies will work with CSAIL scientists to suggest new lines of research and develop real-world applications.

“Developing capabilities in AI and machine learning are key to the future of fields like finance, energy, manufacturing, and health care,” says STL Executive Director Lori Glover. “While the demand for expertise is great, the supply of talent remains small and unevenly distributed. By democratizing the field of AI, SystemsThatLearn@CSAIL is an effort to address that skills gap.”

STL builds on CSAIL’s Big Data Initiative, which developed tools for handling complex datasets. While many machine-learning solutions are trained and deployed in separate phases, STL aims to integrate these processes, focusing on a range of resources to handle distributed data and computing power.

Another goal is to make key aspects of data science less laborious. A 2016 report found that data scientists spend 80 percent of their time collecting and organizing data, and only 20 percent analyzing it.

“By promoting industry interaction with academia, we’re hoping to create new tools and systems that can increase productivity by automating much of the tedious work of data science,” says MIT Professor Samuel Madden, one of STL’s two faculty leads alongside Professor Tommi Jaakkola. “We are already seeing that areas like autonomous vehicles and personalized health care have the potential to transform entire industries.”

In her opening remarks, CSAIL Director Daniela Rus described AI and systems researchers as two communities that would benefit from stronger collaboration.

“Our grand vision is to create a new generation of AI tools that are deeply rooted in systems and that can make those systems better,” Rus said. “My aspiration is to get to a place where machine learning becomes a normal part of what an operating system does.”

One STL project is the data discovery tool “Data Civilizer,” which allows organizations to discover related datasets from thousands of distinct business databases and files. Another is “Model DB,” a machine-learning management system that saves time for data scientists and lets them easily correlate performance on particular training examples with specific model features.

According to STL Technical Director Stephen Buckley, many of the software tools they develop will be released under MIT’s open source license.

“The ultimate aim is to democratize access and use of machine learning tools, without requiring advanced knowledge of the underlying technologies,” says Buckley.

Verizon and American Aerospace Technologies tested a drone designed to provide network coverage in emergencies. Credit: Verizon

April 3, 2017 – April 9, 2017

Public Safety Drones

Police and first responder drones were once a sci-fi fantasy; now they are a reality, appearing with increasing frequency in cities and towns throughout the U.S. In a new study, we have identified nearly 350 police, sheriff, fire, and other public safety agencies in 43 states that have acquired drones in recent years. These drones provide users with a range of opportunities to carry out their missions more safely and effectively than by other means, but they also raise concerns about surveillance and safety.

News

The U.S. military carried out at least 20 air strikes in Yemen in early April. According to a statement by the Department of Defense, the majority of the strikes were carried out by drones targeting members of al-Qaeda in the Arab Peninsula. (Long War Journal)

The U.S. Federal Aviation Administration has banned private and commercial drone operators from flying over 133 military facilities around the country. The restrictions were enacted at the request of the Department of Defense and other U.S. security agencies. (Associated Press)

The U.K. has suspended its campaign of drone strikes against the Islamic State. According to data released by the Ministry of Defence, the Royal Air Force has not conducted any strikes with its MQ-9 Reapers in the past month. The Reapers continue to serve in a reconnaissance and surveillance role. (IHS Jane’s 360)

The U.S. Air Force awarded URS Federal Services a $3.6 billion contract for remotely piloted aircraft services. The Maryland-based company will provide support for testing and training for drone operations in Nevada. The contract, one of the largest drone-related deals in recent years, will stand through 2034. (UPI)

Commentary, Analysis, and Art

At Bloomberg, Justin Bachman examines our data on police drone acquisitions and considers whether law enforcement agencies might one day deploy armed drones.

At BBC News, Chief Constable Jeff Farrar discusses the role that artificial intelligence and drones will play in the future of policing.

A report by the Government Accountability Office found that the Customs and Border Protection agency could continue to do better to integrate its drones into border security operations. (GAO)

At DefenseNews, Jill Aitoro looks at how the U.S. Air Force is training its drone pilots to fly in collaboration with manned aircraft.

Also at DefenseNews, Aaron Mehta writes that the U.S. Strategic Command has issued a new policy for defending U.S. nuclear sites against drones.

At War on the Rocks, Andy Macak and Benjamin Jensen consider historical examples of manned-unmanned teaming.

At Stars and Stripes, Chris Church speaks with military drone operators who are tasked with taking off and landing the aircraft.  

At Buzzfeed News, Nancy A. Youssef writes that U.S. officials suspect that a Russian drone may have been at the scene of the Syrian chemical weapons attack.

At Wired, Adam Rawnsley looks at how militants in Yemen are using drones to disable multi-million dollar anti-ballistic missile systems.

At the Drive, Joseph Trevithick writes that the U.S. military is still training Ukrainian soldiers to fly the RQ-11B Raven drone in spite of reports that Ukraine has ceased using the drone in the field.

At the Strategy Bridge, Elsa B. Kania looks at how China’s military seeks to gain a technological advantage over the U.S. through investment in drones and artificial intelligence.

The Ask DroneU podcast offers advice to drone owners who wish to travel with their drones. (Soundcloud)

At the Drone Radio Show podcast, David Oneal and Sarah Oneal discuss the making of “The Drone Invasion,” a forthcoming documentary about domestic drones. (Soundcloud)

At the Caller-Times, Dr. David Niesel and Dr. Norbert Herzog argue that drones that deliver medical supplies will save lives.

At IoT Agenda, Phil Marshall examines the role that LTE cellular technology could play in enabling autonomous drone operations.

At CNBC, Ryan Brown writes that police in the U.K. are receiving a growing number of complaints about drones.

At The Traverse City Record-Eagle, Dan Nielsen profiles Interactive Aerial, a company developing drones for indoor use.

Director Paul Trillo paired with drone company Aerobo to make a short, one-shot film using a drone. (Drone360)

Know Your Drone

The U.S. Customs and Border Protection agency is soliciting proposals for small unmanned aircraft with advanced sensors capable of facial recognition. (The Verge)

Beihang University in Beijing is reportedly developing a strike-capable reconnaissance drone that it plans to launch in 2018. (IHS Jane’s 360)

A scale model of the the Defense Advanced Research Projects Agency LightningStrike vertical take-off and landing drone completed its first round of test flights. (TechCrunch)

Prox Dynamics is developing a new nano drone that will be about twice the size of its predecessor, the PD-100 Black Hornet. (IHS Jane’s 360)

Japanese camera maker Canon and drone maker Prodrone have unveiled a large multirotor drone designed for search and rescue missions. (Digital Trends)  

U.S. aerospace firm Aurora Flight Sciences is building an improved version of its Orion, a high-altitude, long-endurance drone. (Aviation Week)

Technology firms Fenix Group and Martin UAV have unveiled a sub-55-pound drone capable of providing 4G cellular service. (Unmanned Systems Technology)

Meanwhile, telecom firm Verizon is testing a 17-foot wingspan drone that could provide wireless coverage during natural disasters. (Fox News)  

Amazon has been awarded a patent for a parachute-based damage-avoidance system for drones based on a system it uses for its Blue Origin rockets. (Puget Sound Business Journal)

Canadian startup SkyX unveiled the SkyOne, a industrial fixed-wing drone that can land and take off vertically. (TechCrunch)

Defense One rounds up the most interesting drones on show at the recent Navy League Sea, Air & Space conference.

The U.S. Navy has approved the Snakehead Large Displacement Unmanned Undersea Vehicle for accelerated acquisition so that it can be deployed by 2019. (Defense Systems)

Unconfirmed leaked photographs appear to show a new small consumer drone being developed by DJI called Spark. (TechCrunch) Robotics firm ST Kinetics has announced that its Jaeger 6 family of unmanned ground vehicles are now ready for sale. (Shephard Media)

The Drone Racing League unveiled a new, faster racing quadcopter, the Racer3. (The Verge)

Defense firm Thales is actively marketing its SpyRanger small reconnaissance drone to several countries in the Asia-Pacific region. (IHS Jane’s 360)

The U.S. Navy announced that it is pursuing a concept for collaborative swarming intelligence collection drones called Motley Crew. (Defense Tech)

The U.S. Navy completed a round of test flights of a new variant of its MQ-4C Triton. (UPI)

Drones at Work

Boston public safety officials will deploy a PARC tethered surveillance drone at the starting line of this year’s Boston Marathon. (Boston Herald)

The South Korean military is planning to deploy 10 surveillance drones to monitor North Korean forces. (Yonhap News Agency)

Defense contractor Rafael’s Drone Dome counter-drone system is reportedly operational in an unnamed Asian country. (Shephard Media)

The Seattle Police Department is reportedly investigating a 19-year-old who crashed a drone into the Space Needle for causing a “substantial risk of death or serious physical injury.” (KIRO 7)

Workers building the Xingkang Bridge in China used a drone to tow pilot cables across a river. (Daily Mail)

Bavarian police are investigating a case in which two men reportedly flew a drone over a sunbather on her rooftop. (DW)

Police in Redwood City, California issued an arrest warrant for a 55-year-old drone operator who allegedly interfered with a rescue operation. (Fox 2)

Industry Intel

The U.S. Army awarded Leidos, AASKI Technologies, and AAI Corp/Textron a shared $900 million contract for technical services and field support for the Tactical Unmanned Aircraft Systems Product Office. (DoD)

The U.S. Navy awarded Textron a $14.8 million contract for two fourth-generation Common Unmanned Surface Vehicles. Textron will deliver the systems by 2018. (Marine Technology News)  

The U.S. Navy awarded Pacific Tugboat Service a $669,000 contract for a launch and recovery platform for an unmanned undersea vehicle. (FBO)

The U.S. Air Force awarded HX5 a contract for an small unmanned air system airframe. (FBO)

The U.S. Air Force awarded Composite Engineering a $1.5 million contract for contractor logistics and support for unmanned aerial targets. (FBO)

Rajant will supply Sharp Electronics with the Kinetic Mesh wireless technology for the Sharp Intellos unmanned ground vehicle. (Shephard Media)

L3 Technologies acquired OpenServer Technology, an unmanned undersea vehicle company. (Shephard Media)

For updates, news, and commentary, follow us on Twitter. The Weekly Drone Roundup is a newsletter from the Center for the Study of the Drone. It covers news, commentary, analysis and technology from the drone world. You can subscribe to the Roundup here.

Robot in assembly at Hall 52 on June 26, 2013. File: 062513GR34

There is growing demand for more flexibility in factories and shops. Collaborative robotics, a sub-set of service robotics in labs, manufacturing and material handling, is where the action is today because co-bots are meeting these new demands, while caged legacy robots are not.

Service and assistance robotics, with and without mobility, are an emerging and somewhat futuristic field, albeit one which is developing rapidly. Vision and tactile sensors, safety features, mobility, and simple, fast and intuitive robot training, are all playing important roles in many application areas.

As robots can be trusted to safely work alongside humans and are relatively portable and easy to program, business managers, from all sized companies, begin to imagine uses within their labs, facilities, factories and shops – uses where robots and humans collaboratively work together to improve productivity and efficiency by using the robot where it is better than its human partners, and vice versa.

Definitions, features and applications

The objective of collaborative robotics is to combine the repetitive performance of robots with the individual skills and abilities of people. People are better at seeing and solving imprecise situations; robots can be more precise, powerful, and perform longer.

Wikipedia says a cobot or co-robot (from collaborative robot) is a robot intended to physically interact with humans in a shared workspace. This is in contrast with other robots, designed to operate autonomously or with limited guidance, which is what most industrial robots do. Cobots can have many roles — from autonomous robots capable of working together with humans in an office setting that can ask for help, to industrial robots having their protective guards removed as they can react to a human presence under EN ISO 10218 which requires the robot or robot application comply with one of four collaborative modes: Safety-Rated Monitored Stop; Hand Guiding; Speed and Separation Monitoring; and Power and Force Limitation.

Most of these new co-bots share a growing list of features:

• Affordable cost
• Plug and play
• Intuitive programmability
• Narrow width
• Precise movements as good or better than a human
• Safe to work alongside
  • Complies with ISO 10218 and/or ISO 15066
  • ABB launched SafeMove2, a software sensor suite that, when activited, makes their robots human-safe.
    • Human safe isn’t necessarily collaborative
• Speedy movements as good or faster than a human
• Portability
• ROS

Co-bots are emerging in a variety of verticals:

• Security and surveillance
• Loading/unloading and material handling
• Quality control, testing and measuring
• Guides and sales assistance
• Consumer products
• Industrial tasks (such as):
  • Pick and place
  • Assembly
  • Machine tending
  • Polishing, sealing and deburring
  • Gluing, dispensing and welding
  • Handling and packaging

Numbers

Trade shows tend to feature business solutions 5-10 years ahead of their actual deployment. Bin picking was the trend 10 years ago at robotics trade shows. For the last 5 years, collaborative robotics has been prominently displayed and demonstrated, and the numbers and forecasts showing up in research reports are beginning to prove that the trend is emerging and the collaborative segment of the robotics industry is growing exponentially. In their 2017 Worldwide 10 Robotics Predictions report, IDC said:

Prediction 7: Collaborative Robots — By 2018, 30% of all new robotic deployments will be smart collaborative robots that operate three times faster than today’s robots and are safe for work around humans.

• Transparency Market Research, in their January 2017, 147-page analysis which costs $5,795, forecast that the co-bot market will be worth $95 billion by the end of 2024 and will be growing at a compounded annual growth rate (CAGR) of 30% from now until then.
• Research and Markets, in a November 2016 165-page report costing $3,999, forecast that collaborative industrial robot sales will reach $2 billion by 2021 at an annual CAGR of more than 60%.
• Markets and Markets, in their August 2016, 157-page report which costs $5,650, also forecasts a high CAGR: 60% between 2016 and 2022.

(UR) reflects those phenomenal growth figures. Annual sales have risen from $10 million in 2012 to $95 million in 2016 with revenue expected to be $140 million in 2017.

Beginning from 2017, however, competition will become more prevalent on many fronts from a variety of emerging co-bot companies described below.

Industrial co-bot makers

Most SME’s have a low cost threshold for capital expenditures like robots, thus pricing is a serious consideration. ROI (return on investment) is also important. Universal Robots started a clever advertising campaign using videos showing application use cases and prominently featuring the payback period – from as little as 3-4 months to a year; very respectable in ROI terms. Consequently the wide range of prices for co-bots is most often tempered by the use case(s), ease of use, and ROI. Prices begin at $3,000 for the Chinese-made Dobot, to $11k for the new German Franka, to $29k for an American Sawyer, $35k for a Danish UR10, all the way to $60k for Swiss ABB’s YuMi and up to $100k for Germany’s Kuka LBR iiwa.

Listed below are current and soon-to-launch co-bot providers. This is a moving target, i.e., there are new companies popping up each day. I’m sure to find and add new ones after my trip to Automate/ProMat in Chicago next week.  Follow the company/product links to get detailed technical specifications.

End-of-arm-tooling (EAOT) /  gripper providers

EAOT too is a moving target with multiple new vendors showing up frequently. The list below, however, is a list of companies that actually produce and market grippers for co-bots now. It doesn’t include vision, tool-changer or sensor providers. Follow the highlighted links to get detailed technical specifications.

Resources

• CobotsGuide
• Robotiq
  • eBook: Grippers for Collaborative Robots
  • eBook: ISO/TS 15066 Explained
  • eBook: Collaborative Robot 3rd Edition
• ROS and ROS-Industrial

Researchers have designed and built a device that responds to mechanical stresses by changing the color of a spot on its surface. Image: Subramanian Sundaram

In this age of smartphones and tablet computers, touch-sensitive surfaces are everywhere. They’re also brittle, as people with cracked phone screens everywhere can attest.

Covering a robot — or an airplane or a bridge — with sensors will require a technology that is both flexible and cost-effective to manufacture in bulk. A team of researchers at MIT’s Computer Science and Artificial Intelligence Laboratory thinks that 3-D printing could be the answer.

In an attempt to demonstrate the feasibility of flexible, printable electronics that combine sensors and processing circuitry and can act on their environments, the researchers have designed and built a device that responds to mechanical stresses by changing the color of a spot on its surface.

The components that make up the printable device. Image: Subramanian Sundaram

The device was inspired by the golden tortoise beetle, or “goldbug,” an insect whose exterior usually appears golden but turns reddish orange if the insect is poked or prodded — that is, mechanically stressed.

“In nature, networks of sensors and interconnects are called sensorimotor pathways,” says Subramanian Sundaram, an MIT graduate student in electrical engineering and computer science (EECS), who led the project. “We were trying to see whether we could replicate sensorimotor pathways inside a 3-D-printed object. So we considered the simplest organism we could find.”

The researchers present their new design in the latest issue of the journal Advanced Materials Technologies. Sundaram is the first author on the paper, and the senior authors are Sundaram’s advisor, Wojciech Matusik, an associate professor of EECS; and Marc Baldo, a professor of EECS and director of the Research Laboratory of Electronics. Joining them on the paper are Pitchaya Sitthi-Amorn, a former postdoc in Matusik’s lab; Ziwen Jiang, an undergraduate EECS student; and David Kim, a technical assistant in Matusik’s Computational Fabrication Group.

Bottom up

Printable electronics, in which flexible circuitry is deposited on some type of plastic substrate, has been a major area of research for decades. But Sundaram says that the ability to print the substrate itself greatly increases the range of devices the technique can yield.

For one thing, the choice of substrate limits the types of materials that can be deposited on top of it. Because a printed substrate could consist of many materials, interlocked in intricate but regular patterns, it broadens the range of functional materials that printable electronics can use.

Printed substrates also open the possibility of devices that, although printed as flat sheets, can fold themselves up into more complex, three-dimensional shapes. Printable robots that spontaneously self-assemble when heated, for instance, are a  topic of ongoing research at the CSAIL Distributed Robotics Laboratory, led by Daniela Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT.

“We believe that only if you’re able to print the underlying substrate can you begin to think about printing a more complex shape,” Sundaram says.

Selective signaling

The MIT researchers’ new device is approximately T-shaped, but with a wide, squat base and an elongated crossbar. The crossbar is made from an elastic plastic, with a strip of silver running its length; in the researchers’ experiments, electrodes were connected to the crossbar’s ends. The base of the T is made from a more rigid plastic. It includes two printed transistors and what the researchers call a “pixel,” a circle of semiconducting polymer whose color changes when the crossbars stretch, modifying the electrical resistance of the silver strip.

In fact, the transistors and the pixel are made from the same material; the transistors also change color slightly when the crossbars stretch. The effect is more dramatic in the pixel, however, because the transistors amplify the electrical signal from the crossbar. Demonstrating working transistors was essential, Sundaram says, because large, dense sensor arrays require some capacity for onboard signal processing.

“You wouldn’t want to connect all the sensors to your main computer, because then you would have tons of data coming in,” he says. “You want to be able to make clever connections and to select just the relevant signals.”

To build the device, the researchers used the MultiFab, a custom 3-D printer developed by Matusik’s group. The MultiFab already included two different “print heads,” one for emitting hot materials and one for cool, and an array of ultraviolet light-emitting diodes. Using ultraviolet radiation to “cure” fluids deposited by the print heads produces the device’s substrate.

Sundaram added a copper-and-ceramic heater, which was necessary to deposit the semiconducting plastic: The plastic is suspended in a fluid that’s sprayed onto the device surface, and the heater evaporates the fluid, leaving behind a layer of plastic only 200 nanometers thick.

Fluid boundaries

A transistor consists of semiconductor channel on top of which sits a “gate,” a metal wire that, when charged, generates an electric field that switches the semiconductor between its electrically conductive and nonconductive states. In a standard transistor, there’s an insulator between the gate and the semiconductor, to prevent the gate current from leaking into the semiconductor channel.

The transistors in the MIT researchers’ device instead separate the gate and the semiconductor with a layer of water containing a potassium salt. Charging the gate drives potassium ions into the semiconductor, changing its conductivity.

The layer of saltwater lowers the device’s operational voltage, so that it can be powered with an ordinary 1.5-volt battery. But it does render the device less durable. “I think we can probably get it to work stably for two months, maybe,” Sundaram says. “One option is to replace that liquid with something between a solid and a liquid, like a hydrogel, perhaps. But that’s something we would work on later. This is an initial demonstration.”

“I am very impressed with both the concept and the realization of the system,” says Hagen Klauk, who leads the Organic Electronic Research Group at the Max Planck Institute for Solid State Research, in Stuttgart, Germany. “The approach of printing an entire optoelectronic system — including the substrate and all the components — by depositing all the materials, including solids and liquids, by 3-D printing is certainly novel, interesting, and useful, and the demonstration of the functional system confirms that the approach is also doable. By fabricating the substrate on the fly, the approach is particularly useful for improvised manufacturing environments where dedicated substrate materials may not be available.”

*All images credit: ROBBO

30 teachers arrived, excited to learn. They rolled up their sleeves and placed laptops and Robot kits on the floor. The room filled with excitement (and laughter!) as everyone tried to come up with different solutions on how to create different programs. The results were hilarious; a robot inspired by Darth Vader, a robot that asked everyone to turn the lights off when it was too bright in the room, and a robot that tricked the teacher to leave the classroom during an exam.

Not bad for a day of “work!”

Training, like above, is what we’re all about at ROBBO. ROBBO is a fun and simple way for absolutely anyone to get introduced to the world of robotics and coding. As a part of one of our many projects, we organized a training weekend for the single purpose of introducing teachers to programming and robotics. The teachers started with simple exercises in RobboScratch, a visual programming environment; moving the character, creating series of multiple commands, and learning the advantages of the infinite loop when making programs.

So, what do we mean about classroom robotics? Our educational robotics consist of two different robots; the Robot kit and the Lab. Both robots are ideal for learning programming, robotics as well as skills in problem-solving, mathematics and physics while working in interactive teams. The Lab includes a microphone, LED-lights, light sensor and a slider and is great for experimenting with different elements such as sound or light and numeric values. Our other robot is the Robot kit, equipped with a motor, which is a fun way to explore everyday technology using a touch sensor, proximity sensor, light sensor, line sensors and an LED-light. Our robots are programmed in the visual programming environment RobboScratch, an adapted version of Scratch developed at MIT.

In our earlier example, teachers were divided into separate workshops, working in pairs, or teams of three. We believe it is important to communicate and discuss with others to better understand different programs and come up with alternative solutions if the program doesn’t work in the desired way. The workshops are all based on the exercises from our pedagogical guide, and teachers were given a copy of the guide for their own use. Our guide provides instructions and multiple exercise card (with solutions!) and is free to download here (http://robbo.world/support/).

Our teaching guide is for anyone who wants to learn the basics of programming with the help of ROBBO robotics and RobboScratch. Our pedagogical guide is a comprehensive educational tool with instructions, exercise cards and ideas for creating the ultimate learning experience. It has been developed together with Innokas Network at the University of Helsinki and Finnish teachers and students. The majority of the teachers that participated in the training had only limited knowledge of Scratch or Scratch Junior and, therefore, we started from the beginning.

The pedagogical guide includes an introduction to RobboScratch, Lab and Robot kit as well as up to 28 exercise cards to help you along the way. The exercises are designed to develop necessary programming skills step by step, teaching children to think logically as a software developer would do, which may also be useful in many everyday situations. These are, in particular, the ability to understand the whole, to split a problem into smaller parts, and to develop a simple program to perform an operation. In the initial exercises, students will make a program using a predefined model, but as the practice progresses, they will have more and more space for their own ideas.

By developing new skills, users are encouraged to plan and develop innovations in robotics. The training goal is to learn understand and use technology to invent something new. As the final assignment of the teachers’ training, we asked teachers to form teams of four and come up with a small prank using the different capabilities and sensors of either Robot kit or Lab or simultaneous use of both robots.

If you’d like to to learn more about ROBBO or download our free guide, visit our website: http://robbo.world/support/

Comments from teachers:

“The teaching guide is a great support when learning coding. And I can just hand out these ready-made exercise cards to my students as well!”

“The exercise in the guide are good for understanding the different possibilities you have with the robots, because when you start doing an exercise you come up with more ideas on how to develop a more complicated program.”

“The robots emphasized practicality in the learning process. In addition to programming, ROBBO teaches environmental studies and all-around useful skills, in particular when the exercises of the pedagogical guide are being utilized.”

If you’d like to learn more about classroom robotics, check out these articles:

• How to get started (and progress) in robotics: A quick guide for teens and adults
• Teaching the teachers: Study focuses on how teachers perceive educational robots in classrooms
• Jade Robot: Hands on STEM for kids and classrooms
• Classroom robotics: Motivating independent learning and discovery
• Classroom robots: A great way to get young people started

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

Engineers have designed a microfluidic device they call a “tree-on-a-chip,” which mimics the pumping mechanism of trees and other plants.

Trees and other plants, from towering redwoods to diminutive daisies, are nature’s hydraulic pumps. They are constantly pulling water up from their roots to the topmost leaves, and pumping sugars produced by their leaves back down to the roots. This constant stream of nutrients is shuttled through a system of tissues called xylem and phloem, which are packed together in woody, parallel conduits.

Now engineers at MIT and their collaborators have designed a microfluidic device they call a “tree-on-a-chip,” which mimics the pumping mechanism of trees and plants. Like its natural counterparts, the chip operates passively, requiring no moving parts or external pumps. It is able to pump water and sugars through the chip at a steady flow rate for several days. The results are published this week in Nature Plants.

Anette “Peko” Hosoi, professor and associate department head for operations in MIT’s Department of Mechanical Engineering, says the chip’s passive pumping may be leveraged as a simple hydraulic actuator for small robots. Engineers have found it difficult and expensive to make tiny, movable parts and pumps to power complex movements in small robots. The team’s new pumping mechanism may enable robots whose motions are propelled by inexpensive, sugar-powered pumps.

“The goal of this work is cheap complexity, like one sees in nature,” Hosoi says. “It’s easy to add another leaf or xylem channel in a tree. In small robotics, everything is hard, from manufacturing, to integration, to actuation. If we could make the building blocks that enable cheap complexity, that would be super exciting. I think these [microfluidic pumps] are a step in that direction.”

Hosoi’s co-authors on the paper are lead author Jean Comtet, a former graduate student in MIT’s Department of Mechanical Engineering; Kaare Jensen of the Technical University of Denmark; and Robert Turgeon and Abraham Stroock, both of Cornell University.

A hydraulic lift

The group’s tree-inspired work grew out of a project on hydraulic robots powered by pumping fluids. Hosoi was interested in designing hydraulic robots at the small scale, that could perform actions similar to much bigger robots like Boston Dynamic’s Big Dog, a four-legged, Saint Bernard-sized robot that runs and jumps over rough terrain, powered by hydraulic actuators.

“For small systems, it’s often expensive to manufacture tiny moving pieces,” Hosoi says. “So we thought, ‘What if we could make a small-scale hydraulic system that could generate large pressures, with no moving parts?’ And then we asked, ‘Does anything do this in nature?’ It turns out that trees do.”

The general understanding among biologists has been that water, propelled by surface tension, travels up a tree’s channels of xylem, then diffuses through a semipermeable membrane and down into channels of phloem that contain sugar and other nutrients.

The more sugar there is in the phloem, the more water flows from xylem to phloem to balance out the sugar-to-water gradient, in a passive process known as osmosis. The resulting water flow flushes nutrients down to the roots. Trees and plants are thought to maintain this pumping process as more water is drawn up from their roots.

“This simple model of xylem and phloem has been well-known for decades,” Hosoi says. “From a qualitative point of view, this makes sense. But when you actually run the numbers, you realize this simple model does not allow for steady flow.”

In fact, engineers have previously attempted to design tree-inspired microfluidic pumps, fabricating parts that mimic xylem and phloem. But they found that these designs quickly stopped pumping within minutes.

It was Hosoi’s student Comtet who identified a third essential part to a tree’s pumping system: its leaves, which produce sugars through photosynthesis. Comtet’s model includes this additional source of sugars that diffuse from the leaves into a plant’s phloem, increasing the sugar-to-water gradient, which in turn maintains a constant osmotic pressure, circulating water and nutrients continuously throughout a tree.

Running on sugar

With Comtet’s hypothesis in mind, Hosoi and her team designed their tree-on-a-chip, a microfluidic pump that mimics a tree’s xylem, phloem, and most importantly, its sugar-producing leaves.

To make the chip, the researchers sandwiched together two plastic slides, through which they drilled small channels to represent xylem and phloem. They filled the xylem channel with water, and the phloem channel with water and sugar, then separated the two slides with a semipermeable material to mimic the membrane between xylem and phloem. They placed another membrane over the slide containing the phloem channel, and set a sugar cube on top to represent the additional source of sugar diffusing from a tree’s leaves into the phloem. They hooked the chip up to a tube, which fed water from a tank into the chip.

With this simple setup, the chip was able to passively pump water from the tank through the chip and out into a beaker, at a constant flow rate for several days, as opposed to previous designs that only pumped for several minutes.

“As soon as we put this sugar source in, we had it running for days at a steady state,” Hosoi says. “That’s exactly what we need. We want a device we can actually put in a robot.”

Hosoi envisions that the tree-on-a-chip pump may be built into a small robot to produce hydraulically powered motions, without requiring active pumps or parts.

“If you design your robot in a smart way, you could absolutely stick a sugar cube on it and let it go,” Hosoi says.

This research was supported, in part, by the Defense Advance Research Projects Agency.

Cobalt Robotics has launched their stylish security robot. The robot was designed by Yves Behar and as a fabric covered robot, it’s putting a new spin on soft robotics! Behar’s goal was to create a robot that didn’t conform to Hollywood stereotypes but instead as an augmentation of human ability and an enhancement to the human environment.

“Creating the right form for Cobalt is crucial to its success. As a service for security and concierge, it becomes part of an office culture. This balance between approachability and discretion became a thematic challenge throughout the design process. We decided that the robot should not adopt a humanoid personality. Instead, it should aesthetically align with the furniture and décor of the office environment. The Cobalt robot’s semi-cylindrical self-driving mechanism, sensors and cameras are covered by a tensile fabric skirt. This helps maximize the access and usability of the internal technologies, creates airflow to prevent overheating, and conveys a soft and friendly persona.” said Behar.

Cobalt Robotics was founded by Travis Deyle and Erik Schluntz, former GoogleX and SpaceX engineers. After a thorough analysis of the various emerging service robotics industries, they focused on the security industry rather than retail, logistics, or hospitality, because the economics made the most sense.

“A fleet of Cobalt robots is comparable to an extremely competent guard with superhuman capabilities and omnipresent situational awareness across an entire organization,” said Cobalt CEO and Co-Founder Travis Deyle.

Security is necessary but it’s often cost prohibitive for companies to provide a 24-hour security presence. The Cobalt robot allows security to have a presence so that they can remote in, see what’s going on, look for intruders, and it also serves a purpose for the employees. If something bad happens, it’s currently on the employee to either call the police or fumble around looking for the security number of their corporate office. Cobalt lets them go up to the robot and immediately get a person to talk to.

“One of the core fundamental values of Cobalt is to enable human-to-machine interactions,” said Erik Schluntz, Cobalt CTO and Co-Founder. “The way we do that is designing a robot to interact with and around people.”

Cobalt worked with world-renowned designer Yves Behar and his company, fuseproject, to define the form and interactions. The balance between approachability and discretion became a thematic challenge throughout the design process.

“As robotics and AI touch more areas of our daily lives, the role of the designer is to make these technologies accessible, augment our abilities and create our best possible future,” says industrial designer Yves Behar. “The Cobalt design is very different in that it is made of fabric and aluminum, an aesthetic more akin to furniture and workspaces than a Hollywood robot.”

Using extremely capable sensors (day-night 360° cameras, thermal cameras, depth cameras, LIDAR, etc.) and cutting-edge algorithms (machine learning, semantic mapping, novelty detection, and deep neural networks), the Cobalt robot detects and flags security-relevant conditions or anomalies — things like people, doors & windows, suspicious items, items that have moved or changed, and water leaks. Bloomberg Beta and Promus Ventures led Cobalt’s seed round, with participation from Haystack, Subtraction Capital, Comet Labs and various individual angel investors.

“Our fund has been searching for the most immediately useful applications of robotics, and Cobalt has found one. We look forward to seeing safer and better workplaces, served by Cobalt,” said Roy Bahat, head of Bloomberg Beta.

The Zwentendorf Nuclear Power Plant in Austria was completely built but never put into operation. Reactor supervision and decommissioning is one important operational area for robots in the RN domain.

There is significant potential for the use of unmanned vehicles in scenarios involving radiological and nuclear (RN) threats. The European Reference Network for Critical Infrastructure Protection (ERNCIP) has therefore established a thematic group on the protection of critical infrastructure from Radiological and Nuclear Threats (RNTs).

The group looks at issues such as standardisation of deployment protocols, response procedures and the use of unmanned systems. Possible threats involve measurement and sampling scenarios that are too risky for humans to carry out, also in the event of criminal or unauthorised acts involving nuclear or other radioactive material. Situations envisaged for the use of unmanned ground vehicles (UGV) are:

• Reactor supervision and related accidents, such as Chernobyl and Fukushima;
• Illicit release of radioactive material (radiological dispersion devices and dirty bombs before or after an explosion);
• Search of sources out of regulatory control;
• Long-term measurements.

Lessons learned from incidents such as Fukushima and Chernobyl, as well as from decommissioning of old nuclear power plants, show that robots have certain advantages. Robots can operate in areas with high radiation, danger of explosives, for example Boiling Liquid Expanding Vapour Explosions (BLEVE), collapsing structures, Improvised Explosive Devices (IED), booby traps, aggressive chemicals (e.g. Chlortrifluorid) and extreme heat. Additionally, they can manipulate the environment and take samples. Robots can also be used for long-time surveillance of contaminated areas and for monitoring the movements of a threat using real-time data from mobile sensors.

Robotics in the RN domain – applications and standards

The ERNCIP RNTs group focusses on possible applications. The identified scenarios can be separated in two categories. First, there are prevention scenarios where unmanned systems can be used to prevent incidents involving radioactive material and deterrence. Second, there are response scenarios where unmanned systems gather information after incidents with radioactive material occurred. We further identified several tasks for unmanned systems:

• spatial mapping of RN sensor data (exploration, change detection);
• searching for RN sources (active sensing, isocurves, hotspots);
• sampling (air, sweep or material sampling);
• 3D infrastructure mapping (situation awareness & assessment).

Possible applications for robots in the RN domain: taking samples of potentially hazardous materials (left) or measuring and searching for radiological and nuclear sources (right).

Another important finding was that no standards, best practices or norms for sampling or taking measurements with unmanned systems have been systematically developed thus far. Therefore, a first set of potential standards for unmanned systems in RN measurement scenarios was compiled. A widely accepted standard collection of frameworks for robot software development is the Robot Operating System (ROS). Further important standards concerning communication with robots and control of unmanned systems are the Battle Management Language (BML), InterOperability Profile (IOP) and Joint Architecture for Unmanned Systems (JAUS). Furthermore, there are efforts for standardisation in the International Electrotechnical Commission (IEC) regarding international standards for RN measurements with unmanned systems.

Trials and competitions – great way to raise interest in RN related robotics

The results of the ENRCIP RNTs group pointed to an inherent need for a practical element shaping and enforcing the standardisation process in the robotics community. Unfortunately, it was also obvious that there is currently little to none interest of the academic robotics community in the RN field. There is, however, an effective means to address large robotic communities: the field of robotic competitions. Since robots usable in RN scenarios most probably have to be outdoor/off-road systems, the RNT group, thus, decided to set up an RN scenario at a popular outdoor robotics competition.

The group also identified a huge gap between what the R&D community is able to deliver, the existing industry state of the art and the user requirements (if properly determined). This includes the complete absence, non-observance or non-compliance of standards, best practices and norms. Naturally, the R&D community does not have a focus on standardisation, manageability, sustainability, robustness or reliability. Again, robotic competitions can be used as method to bring together users, academia and industry. The users can visualise their needs in the form of real world scenarios to be tackled by the R&D community and industry. At the same time, the industry is able to mingle with the R&D community. Thus, a constructive way to push forward unmanned systems in RN scenarios might be the utilisation of trials and challenges.

The European Land Robot Trial 2016 took place in Eggendorf, Austria. For the first time, a RN task with real radiation sources was included and attracted robot teams from all over the world.

In 2016, the European Land Robot Trial (ELROB) was hosted by the Austrian Army in the Tritolwerk in Eggendorf. The Tritolwerk is an old ordnance factory, now used for CBRNE training and training for emergency services. These premises gave the perfect setting for a very special scenario: Reconnoitring of urban structures with a focus on radiological and nuclear measuring and mapping. This was the first real world live scenario with strong radiation sources (Co60, 2,8GBq each) on a robotics competition ever! The task involved detecting an unknown number of hidden radiation sources. The robotic systems had to measure the radiation, display measurements to the operator, acquire imagery and mark the sources in an online-built map representation. Ten teams participated in the scenario. Since this was the first try of such a scenario, the expectations were curbed. However, the teams performed reasonably well, and most presented RN readings. It turned out that many teams did not have enough background knowledge on radiation detection to produce suitable results.

European Robotics Hackathon – fully focused on RN tasks

Based on these circumstances a new robotic trial, the first European Robotics Hackathon (EnRicH) was created and will take place in June 2017. The scenario at EnRicH is inspired by the radiological reconnaissance task at ELROB 2016 and has a similar setting, indoor search for radiation sources and 3D mapping, but with an additional manipulation task. The event will be accompanied by a R&D workshop which is planned and conducted by the ERNCIP RNTs task group. The workshop has a focus on standards for unmanned systems in the RN field of application. The EnRicH hackathon will take place in the inoperative nuclear power plant (NPP) in Zwentendorf, Austria. The boiling water reactor of NPP Zwentendorf has been fully completed but never put into operation. In Zwentendorf areas are easily accessible which in other NPPs can only be visited under severe difficulties. In an active nuclear power plant extensive safety precautions are needed for human personnel due to the high level of radioactivity. Instead, in the NPP Zwentendorf engineers have transformed the plant and turbine halls into a training centre. Repair and dismantling measures but also critical incidents and disaster scenarios can be trained under realistic conditions.

Naturally, a nuclear power plant contains areas which cannot be safely entered by human personnel on one hand, due to inherent radiation like in the reactor building, and on the other hand due to technical problems or accidents leading to an unpredictable and uncontrolled radioactive contamination of parts of the plant. In any case, a robotic system doing an exploration of the scene would be helpful. This is the basic setting for the newly created European Robotics Hackathon.

In EnRicH, the exploration task consists of three sub-tasks: first, a digital 3D map of the area of interest has to be built; second, radiation and its sources must be detected, measured and marked inside a digital map; and, third, if a system is equipped with a manipulator device, some radioactive material has to be handled. All collected information has to be passed on to a reach back team for further evaluation.

The interior of the Zwentendorf Nuclear Power Plant provides the setting for the first European Robotics Hackathon (EnRicH). Robots will have to build a conventional 3D map of the scene, measure and map radiation sources, and manipulate hazardous material.

During the trial, major challenges are waiting for the participating systems and teams: First, severe mobility problems are caused by the typical interior of a power plant with elements like low or no light, closed doors, dead ends and blockings, sharp turns or steep stairs. Second, major difficulties for any kind of communication approach can be expected due to massive concrete walls and metal interiors. However, as a fall-back solution the organizers provide a standard wireless communication infrastructure for the teams. And, finally, due to the active radiation sources inside the scenario nobody will be allowed to accompany the robots, making robustness an essential prerequisite for the systems. However, the scene will be equipped with cameras, allowing some basic supervision for the operators from outside.

Hence, the problems of robots in hazardous operations and emergency response, especially when involving RN components, are diverse. Trials like ELROB and EnRicH reveal many remaining technical challenges, such as communication, sensors, situational awareness, mobility/locomotion and robustness, which often accrue from the fact that these systems have not been used and tested enough. There are still a lot of lessons to be learned.

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

• Russia looks inward and outward at Moscow’s 2013 Open Innovations Forum
• Mining and nuclear decommissioning: Robots in dangerous and dirty areas
• American nuclear materials storage site guarded by robots
• Disaster response robot will inspect the damaged Fukushima nuclear reactor building

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

TERESA project. Photo credit: Claire Cocano

TERESA is a 3-year research project funded by the European Union and carried out by six institutions from four European countries. Its goal is to develop a new socially intelligent semi-autonomous telepresence system.

A telepresence system consists of an internet-connected mobile robot equipped with a video screen, speakers, and microphones.  A remotely located pilot sitting at a computer can control the robot and use it to interact with people at the robot’s location.

Telepresence systems offer a number of advantages over traditional teleconferencing solutions such as Skype. The robot acts as an avatar for the pilot, allowing the pilot to appear much more present to people around the robot. In addition, because a telepresence robot is mobile, it enables spontaneous interaction, such as mingling at a cocktail party, that would not be possible with Skype.

TERESA project. Photo credit: Claire Cocano

However, existing telepresence systems suffer from a key limitation. They require the pilot to manually execute many behaviours that would happen automatically and effortlessly if the pilot was physically present.  These include navigating through groups of people in a socially appropriate way, maintaining a socially appropriate distance and orientation to others, and maintaining socially appropriate eye contact.

The need to manually execute these low-level behaviours at the same time as selecting high-level behaviours, such as whom to talk to and what to say, can afflict the pilot with cognitive overload, which in turns leads to poor quality social interaction.

In the TERESA project, we have created a new semi-autonomous telepresence system that automates low-level decision making, thereby freeing the pilot to focus on the social interaction itself. TERESA can autonomously navigate through groups of people in a socially intelligent way and approach a specific person selected by the pilot. During conversation, TERESA can also maintain a socially appropriate distance from those around the robot and set the height, orientation, and tilt of its video screen so as to facilitate that conversation.

TERESA is not just intelligent but socially intelligent, thanks to advances in multi-modal perception, machine learning, and robotics developed in the project by an interdisciplinary team of computer scientists, engineers, sociologists, and experts in human-robot interaction.

Working with an elderly day centre in France, we have repeatedly validated TERESA with dozens of elderly subjects. Our results show that semi-autonomous telepresence systems can play a key role in improving the quality of remote interaction. Although TERESA is just a proof of concept, it illustrates the potential of social intelligence to transform telepresence systems and other robots as well.

If you enjoyed this article, you may want to read more about telepresence robotics:

• Telepresence robots help chronically ill kids maintain social, academic ties at school
• Telepresence has come a long way, where do we go from here?
• Personalizing telepresence in service robots
• ORIGIBOT: An affordable telepresence robotic test platform with arm and gripper
• Telepresence, or tele-existence? 4 devices seeking to break down barriers to remote presence

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

CES 2017 has come and gone. As a first-timer in attendance, I couldn’t help but marvel at the featured robots and all robotics related gadgets, toys, start-ups, wearables, and AI coming to market. I’ll conduct a post-event wrap up shortly, but in the meantime, please enjoy a selection of images seen on the floor.

Divergent 3D supercar

The connected home and car, Alexa and Ford working in partnership to streamline and connect your life.

LG’s Helper Guide Robot to help you find your gate and remind you when your plane is scheduled.

LG’s Hub Robot helper that can control your smart home devices, play music, and offer advice on commuting times.

Home helper robot in the Chinese market.

Denso’s robotics cafe made sure everyone got through the day well caffeinated at CES.

Jade Le Maître with HEASY hospitality robot, from Hease robotics.

Kuri home robot saying hello!

Meet the dream team of women at Mayfield Robotics who made Kuri possible! (left to right: Kaijen Hsiao, CTO; Stephanie Lee, Engineer; and Sarah Osentoski, COO).

TechCrunch speaking with Mike Beebe from Mayfield Robotics.

Silas Adekunle presents his gaming robot, MekaMon.

VR gaming at the Dell experience.

Robart AI solutions in your home.

In the startup area, robot teacher to help children learn.

WowWee chip robot dog toy.

The White House released a new report on the ways that artificial intelligence will transform the US economy over the coming years and decades.

Below is shortened version from the original post.

On December 20, In order to ready the United States for a future in which artificial intelligence (AI) plays a growing role, the White House released a report on Artificial Intelligence, Automation, and the Economy. This report follows up on the Administration’s previous report, Preparing for the Future of Artificial Intelligence, which was released in October 2016, and which recommended that the White House publish a report on the economic impacts of artificial intelligence by the end of 2016.

Accelerating AI capabilities will enable automation of some tasks that have long required human labor. These transformations will open up new opportunities for individuals, the economy, and society, but they will also disrupt the current livelihoods of millions of Americans. The new report examines the expected impact of AI-driven automation on the economy, and describes broad strategies that could increase the benefits of AI and mitigate its costs.

AI-driven automation will transform the economy over the coming years and decades. The challenge for policymakers will be to update, strengthen, and adapt policies to respond to the economic effects of AI.

Although it is difficult to predict these economic effects precisely, the report suggests that policymakers should prepare for five primary economic effects:

• Positive contributions to aggregate productivity growth;
• Changes in the skills demanded by the job market, including greater demand for higher-level technical skills;
• Uneven distribution of impact, across sectors, wage levels, education levels, job types, and locations;
• Churning of the job market as some jobs disappear while others are created; and
• The loss of jobs for some workers in the short-run, and possibly longer depending on policy responses.

In the cases where it is possible to direct mitigations to particularly affected places and sectors, those approaches should be pursued. But more generally, the report suggests three broad strategies for addressing the impacts of AI-driven automation across the whole U.S. economy:

1. Invest in and develop AI for its many benefits;
2. Educate and train Americans for jobs of the future; and
3. Aid workers in the transition and empower workers to ensure broadly shared growth.

Read the entire White House summary here.

Download the PDF report here.

You can also read these articles about AI and the White House:

• White House launches public workshops on AI issues
• White House releases reports focusing on opportunities and challenges of AI
• White House economic report looks to robotics for the future
• We the Geeks: Whitehouse hangouts celebrate robots, maker culture and more

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

A recent article in The Washington Post by Morgan Stanley strategist and author of “The Rise and Fall of Nations” Ruchir Sharma, provides a nuanced overview of the issues of jobs, robots, productivity and income disparity. 

In the article, Sharma suggests that because the labor pool isn’t growing fast enough to support our needs, it may not be long before economists worry about a global shortage of robots to fill those needs.

“In many industrial countries, from Germany to Japan to South Korea, growth in the working-age population has already peaked, acting as a drag on the economy. Widely overlooked, however, is the fact that the population-growth slowdown is unfolding even faster in the emerging world.”

China, the most prominent of those emerging countries, is already feeling the effects of four disruptive population trends:

1. China’s working-age population growth just turned negative and China is expected to lose 1 million workers each year for the foreseeable future.
2. Of those coming of working age, because of education and other social reasons, they don’t want to work in factories.
3. China’s elderly share of the population is rising twice as fast as in the U.S. and four times faster than in France. Unlike France and the U.S.
4. Given the widespread political backlash against immigration, compensatory immigrant increases to offset ageing workforces are unlikely.

Sharma cited an instance where Daniel Kahneman, the Nobel prize-winning psychologist/economist who wrote “Thinking, Fast and Slow,” a 2011 best seller, had occassion to comment on the subject:

“Asked by an alarmed dinner companion about the threat robots posed to jobs in China, Nobel economist Daniel Kahneman responded: “You just don’t get it. In China, the robots are going to come just in time.” No wonder Beijing now offers heavy subsidies to companies involved in industrial automation.”

Strategic long-view planning such as that exhibited by the Chinese series of 5-year plans focused on bringing robotics to China, creating an in-country robotics industry, and expanding the use of robots to provide social assistance in addition to industrial production, is being replicated in Japan, Korea and throughout the EU.

It remains to be seen how this will play out in the U.S.

If you enjoyed this article about robots and jobs, you may also want to read:

• US auto industry installed 135,000 robots and added 230,000 jobs
• What coachmen from the 1920s can tell us about robots and jobs
• Stop talking about bringing jobs back from China
• ‘Robots or jobs’ is key focus of #ERF2015
• Obama connects robots to jobs in State of the Union address

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

Source: IFR.org

In the last six years, (2010–2015), according to the IFR (International Federation of Robotics), US industry has installed around 135,000 new industrial robots. The principal driver is automation in the car industry. During this same period, (2010–2015), the number of employees in the automotive sector increased by 230,000.

This news affirms the conclusions of a study conducted by the market research firm, Metra Martech, “Positive Impact of Industrial Robots on Employment,” that there will be growth in robot use over the next five years resulting in the creation of one million high-quality jobs around the world.  “Robots, in addition to the auto industry, will help to create jobs in some of the most critical industries of this century: consumer electronics, food, solar & wind power, and advanced battery manufacturing to name just a few.”

“The rapid rise of robot use in the United States is impressive for several reasons,” said Jeff Burnstein, President of Robotic Industries Association.

1. The industry’s largest user, the automotive industry, has accelerated its purchases of robots and at the same time created more jobs in the manufacturing process.
2. There has been strong growth in the use of robots in general industry, as robots further penetrate industries such as life sciences, warehousing, and semiconductor and electronics manufacturing.
3. The use of robots is rising in small and medium sized companies who see robotics as a key factor in improving productivity and product quality in order to stay globally competitive. We expect these trends to continue well into the future.

According to the International Federation of Robotics, car manufacturers and component suppliers will continue to be heavy users of robots. In addition, more and more new companies specialized in electric or autonomous vehicles that are starting up in the United States and are in need of modern and efficient production facilities. The electronics industry continues to be the fastest-growing emerging industry for industrial robots in the United States (2014-2015 = +41%). Increasing numbers of orders can also be expected from the metals and machinery industry, the rubber and plastics industry, the pharmaceutical and cosmetics industry, and the food and beverage industry.

Credit: “Brewing Beer with Robots” Brew Age/YouTube

Craft brewing could be the perfect industry for collaborative robots. But, does automation mean losing your artisan status? We find how craft breweries can use robotics to scale-up their business without compromising on quality.

Robotics and craft beer don’t sound like they go together, right?

Think of craft beer and you think of a lone artisan brewer, stirring a huge pot of boiling malt with a long wooden spoon. Think robotics, on the other hand, and you probably think of a huge factory with automated conveyor belts, rivers of bottles and an army of robot arms.

In the past, automation meant mass produced beer — not anymore. Robots are coming to craft brewing.

Craft beer’s popularity is a problem for brewers

Credit: Robotiq

We’ve been thinking a lot about beer here at Robotiq because we recently tried our hand at home brewing. We made a limited edition batch of DoF Lager especially for members of the DoF robotics community. Yeah, we like a challenge at Robotiq — lager is one of the trickiest beer styles to get right.

Our brewing experience got us thinking about the craft brewing industry. Craft beers are now popular in many countries. This is great because it means that quality beer is everywhere. However, it’s popularity also causes a big problem for brewers. How can you scale up a craft brewery while staying true to your artisan spirit?

Ben Dobler is the Brewing Innovation Manager for Windmer Brothers. He explains a familiar problem for brewers:

“You build your perfect brew house and then, all of a sudden, you can’t make enough beer so you increase your fermentation capacity. Then you have to increase your cellar capacity. Well now you can brew it, you can cellar it, but you can’t package it fast enough. So, now you need to increase your packaging efficiencies, your racking line efficiencies, speeds, size. Then you start that cycle back over again.”

The more popular your beer becomes, the more people want to buy it. Sooner or later, all manufacturing businesses hit a bottleneck. For brewers, that bottleneck could, quite literally, be in the neck of a bottle.

How to use robots to scale-up your brewery

Earlier this year, I visited a craft brewery where they do everything by hand. It’s a small brewery, but not tiny; they can brew over 1500 litres per day. One thing that struck me, as an engineer, was that they did all their bottle capping with a bench capper (which caps two bottles at a time by pushing down hard on a lever). If this were my brewery, I thought, I’d automate that task.

Credit: “Why I Automate – Widmer Brothers” A3/YouTube

There’s a real danger of musculoskeletal disorders when performing this type of repetitive action hundreds of times a day. Also, the task doesn’t add any value to the beer, it’s just a necessary step in the bottling and packaging process. Surely, a perfect candidate for automation.

Craft brewers are often suspicious of any type of automation, which I understand. There’s a worry that using robots will mean that you can no longer call your beer an artisan product; however, automation doesn’t mean you have to make generic beer. In fact, automation can free you up to make even better beer.

“When we talk about automation, in some circles within the craft beer world it’s almost a taboo word, which to me is kind of baffling.” Ben Dobler, Windmer Brothers

In 2015, Windmer Brothers made a brave choice to add robotics to their craft brewery. They added a KUKA manipulator to help with palletizing, which is also a non-value-added process.

Ben makes a good point in this video. If you give the repetitive tasks to a robot, you have more time to focus on other aspects of the brewing process — like coming up with new beer recipes!

As we are also starting to see in the artisan bread, farming and coffee industries, robotics is converging with the artisan food and beverage sector.

The robot used by Windmer Brothers was big — requiring a lot of space and restricted access — but collaborative robots are much smaller and are designed to work alongside humans. They can fit right alongside your existing equipment.

How to start using robots in your craft brewery

As with any investment, it’s a good idea to consider specific applications before deciding to buy a robot. A good place to start: How to Get Started With Collaborative Robots and the eBook How to Shop for a Robot. Use the worksheet in the learning kit to assess some possible tasks for the robot.

Most craft brewers who have started using robots have applied them to packaging processes. Packaging applications are a great place to start because:

• Packaging is a non-value-added process: The beer is already made at this stage so there is no chance of the automation compromising on quality.
• Packaging has a high risk of musculoskeletal disorders: As anyone who has packed beer knows, it involves a lot of repetitive movements. This might not be risky when your production is low; but the more beer you make, the higher your risk of repetitive strain injury (RSI).
• Hand packaging produces breakages: Packing bottles into a box is a simple task, but after you have done it over 300 times (and you’re only halfway through the batch) you are much more likely to drop a bottle or two. One big advantage of robots is that they don’t get tired.
• Packaging usually doesn’t require extra technology: Some of the tasks which you can automate in craft breweries will require extra machines (like automatic labeling machines or semi-automatic bottle cappers). However, packing applications are usually going to be palletizing or simple pick-and-place tasks, which require no extra sensors or equipment. This makes them a great first robot application.

In the next article, we will discuss specific applications in a craft brewery which are great for robots. None of these tasks involve touching beer, so your artisan status is safe. However, as the guys from Dirty Robot Brewworks show in this video, you could also use robots in the cooking if you really wanted to.

Source: HBO, Westworld

Please note: The following article may contain spoilers up to Episode 5 of Westworld.

HBO’s Westworld (on Sky Atlantic here in the UK) is progressing nicely, though even now at five episodes in it’s probably a little too early to start speculating about what is going on exactly. However, at the risk of casting wild speculations that hindsight later proves naive, one character that is particularly interesting: Anthony Hopkin’s Dr. Robert Ford.

I mentioned in my last post on Westworld that Ford’s name is meant to make audiences recall Henry Ford, the twentieth-century industrialist and whose name has become synonymous with automated mass production and consumerism. Though Ford did not invent the assembly line, his implementation of the industrial mode of production conjures images of the sort of alienated labour that has been held responsible for the dehumanisation of human beings since the dawn of the Industrial Revolution.

But Henry Ford can also be regarded as a cousin of a particular kind of character we’ve seen repeatedly in fiction and film over the centuries (specifically, the centuries since Western thinkers started exhibiting anxiety about the effects with how we make things – industrialisation – and the accompanying way of thinking – rationalism). Frankenstein, as I’ve said before, is the grandfather; Faust is perhaps the older, more distant relative; Prometheus is their icon.

We’ve come to think of these figures as the archetypical mad scientist: the unhinged narcissist, a victim of his own hubris, who simultaneously uses the clarity of science and rationalism on the one hand and maniacal passion on the other. The mad scientist desires to stand with the gods and to create new life, but inevitably, builds a monster that will break free of its creator’s control and return to destroy him and everything he holds dear. [I’ve used the male pronoun intentionally for the mad scientist because they are invariably male. I would LOVE if anyone could provide an example of a female mad scientist. Comment below, please.]

Source: Rotwang, from Lang’s Metropolis (1927)

Though Frankenstein is probably the best known of these mad scientists, his monster was biological, not mechanical. But from the very first stories about robots, mad scientists have been portrayed as the crazed geniuses that unleash their creations upon the world. Rotwang, of Fritz Lang’s 1927 Metropolis created a new template who can count amongst his descendants, including Dr. Edward Morbius, Dr. Eldon Tyrell and  Nathan Bateman.

But as those last two examples demonstrate, the mad scientist has undergone something of a transformation of late. And we can give some credit for this to none other than Isaac Asimov. Asimov, as we know from his writings – and from his short essay on ‘The Frankenstein Complex’ – was against this persistent of archetypes of robotic monsters; he was also unhappy with the portrayal of roboticists as the mad scientist and sought to normalise the job so that the public would regard roboticists as just ordinary people with ordinary occupations. Asimov’s robot stories are devoid of villains, they are populated with scientists, engineers, ‘robot psychologists’ all simply going about their business, trying to fix robots that have gone awry. And the robots in Asimov’s stories are shown to be simply ‘malfunctioning’; they are not acting out of any malice caused by newly achieved self-awareness and a subsequent desire to sadistically destroy the human race. Asimov’s robots simply have problems in their programming, problems that have rational explanations and can be addressed using a similar application of reason.

If only all science fictions writers were as committed to such lofty ideals. Asimov’s stories are unique because they are different in terms of structure. These are not traditional stories of conflict, of good guys in white hats battling black-clad evil-plotters. Some might argue that Asimov’s stories, for all their noble intentions, lack something… excitement, maybe… without these usual elements. Regardless, most science fiction writers since have been unable to resist the temptation to put villains and more traditional story-arcs back into their robot narratives.

No mad scientists here.

Now post-Asimov, however, in a world full of scientists, we have come (more or less) to accept the nobility of science and those strange professors that practice those magical arts. The likes of Frankenstein and Rotwang seem to be in short supply – at least, we don’t have anyone more than ‘slightly eccentric’ at our Sheffield Robotics lab. And hardly anyone wears a long white coat. (There’s a lot of plaid, though.)

But in such a world, where does a sci-fi writer look when trying to imagine the Baddie? Where can writers find a suitable antagonist against whom the hero can do battle and audiences can fist-pump their relief when they are finally defeated?

The image we might have once had of the isolated, mad genius working (virtually) alone in a dungeon converted into a laboratory (a very intriguing transformation in its own right) no longer suffices for Tyrell and Bateman and their like. The modern scientists are much happier in clean, ultra-modern research facilities or skyscraper. These new scientists are not aided by a sole hunchback named ‘Igor’ but are rather backed by an entire corporate machine,  with boards of directors, capital, public relations teams and  (often) military contracts.

This transformation of the villain in robot-monster movies, from the individual mad scientist to the soulless, harmful corporation, represents an important shift in what we, as a society, fear and the root of our anxieties.

What we seem to be seeing in Westworld – and remember, it is far too early to say with any certainty, so this is really not much more than an historically-informed fan-theory – is this shift from the mad scientist to the corporate villain being illustrated right before our eyes.

On the one hand, we have Dr. Ford. He’s old now and has been at the park since its inception [See what I did there – ‘Inception’…?] . In fact, as he explains in Episode 3, he was there before the park opened together with his partner, the mysterious ‘Arnold’. Both Ford and Arnold are presented as scientists cut from the ‘mad’ lab coat. It’s said that Ford is ‘chasing his demons over the deep-end’. Ford, echoing his forefather, Frankenstein, wistfully speculates that one day ‘We can …perhaps one day even resurrect the dead.’ When Abernathy says in Episode 1 that his ultimate goal is to ‘meet his maker’ he echoes many other famous monstrous creations, from the original Frankenstein’s creature to Roy Batty, Tyrell’s rouge android.

Harkening back even further, to the archetype’s Faustian roots, Ford says ‘You can’t play God without being acquainted with the devil’. Ford explains to Bernard the nature of his art: ‘We practice witchcraft. We speak the right words, and we create life itself out of chaos’.

And so on. And of course, Arnold looms over all of this, perhaps literally the deus ex machina, the god from/in the machine, may yet to overturn whatever agenda are being set and thwart whatever objectives others imagine Westworld realising.

But lurking behind Ford, behind Arnold, is this as-yet unidentified corporate agenda. As Theresa Cullen explains to the ambitious Sizemore: ‘This place is one thing for the guests, another thing to the shareholders and something completely different to management.’ (Do you ever feel that the names in Westworld might actually all be allegorical, in one way or another? It makes guessing what might happen next fun…).

Photo: Tyrell Corporation HQ – Blade Runner (1982)

Corporations are the perfect villain for movies about robots, especially in the twenty-first century. Mad scientists are too messy, too human. They are driven by demons and passions and hubris; they are much more suited to another age, to classical and Romantic tales. Frankenstein’s manor and dungeons, hunchback servants and the macabre use of dead bodies all reek of Gothic sensibilities. Corporations, on the other hand, are wonderfully rational. They are not ‘evil’ – they are completely emotionless, disinterested in the consequences for imperfect and insignificant lifeforms like human beings (or the environment). Like the robot monsters to which they give birth, they are motivated not by unconscious or animalistic impulses; what drives the corporation is nothing other than a completely predictable, rational goal: the accumulation of wealth. (As this picture suggests, though, we might not be entirely free of Gothic imagery just yet.)

If films about robot monsters are expressions of our anxiety that humans are becoming too much like machines and vice versa (see this paper I wrote for a slightly different version of this argument), then the corporation is the ideal villain into which we can project this anxiety. The corporation is like a networked machine, made up of many interrelated nodes; eliminating one of these cogs does not bring the machine to an end. It behaves like the Terminator, ruthlessly pursuing its single goal, with no consideration for collateral damage or the pettiness of things like human emotion, or life.

Furthermore, if human beings are becoming less human in our rational, (post-)industrial world, the corporation not only represents this transformation but facilitates it. The corporation provides a legal framework and a moral justification for our dehumanisation. The ubiquity of corporations in our economic (social) life means that we are all subject to their influence, and are all in danger of being dehumanised in its machinations. The very foundations of human society become not based on human relations but relations between signs, or figures on a spreadsheet. Such structures mean that the role of individual decision-making is removed from the equation: human beings do not decide to ‘go black hat’ and be evil. But nevertheless, whatever decisions we make, we live a world less-human and less-humane, in spite of ourselves. Just as demons once provided scapegoats for human immorality, we can absolve ourselves of responsibility for our dehumanisation with the knowledge that we, like the corporations and their machines, are pre-programmed by a system whose script we are unable to extricate ourselves.

It is still too early to tell if Westworld will actually go down this road, if it will continue to offer this post-Asimov twist. (The first series of Channel 4’s Humans also seemed to suggest that this might go in similar direction, so it will be interesting to compare how both or either deal with this issue.) It’s perhaps folly or even hubris at this point to speculate, such are the rich possibilities. I can’t wait to see how this develops, however, and who is revealed to be the ‘villain’ of Westworld, or if it will eschew any such traditional narrative structures.

If you liked this article, you may also enjoy reading more about Westworld:

• The new Westworld: Humanizing the un-human, or dehumanizing humankind?
• Why watching Westworld’s robots should make us question ourselves
• Robohub Digest 10/16: White House reports, Westworld, ESA space race and Robot Launch

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

Source: YouTube

In October, the U.S.-China Economic and Security Review Commission released a report, China’s Industrial and Military Robotics Development, prepared by the Defense Group, Inc. at the Commission’s request. The report examines the development of China’s unmanned industrial, service, and military robotics systems, such as drones and driverless cars, and the economic and national security implications of these trends for the United States.

China’s rising demand for high-end robotic components and service robots as well as U.S.-China bilateral artificial intelligence research present potential markets and collaboration opportunities for the United States. But the inherently dual-use functions of industrial and service robotics strengthen China’s commercial and military production and robotic capabilities, potentially improving China’s defense industry and eroding U.S. military advantages. In addition, the application of artificial intelligence can enhance the learning capabilities and the military effectiveness of unmanned systems such as drones, which may undermine U.S. technological and military advantages.

Overall, the report advocates that the U.S. government:

1. implement the recommendations of the Advanced Manufacturing Partnership 2.0 Steering Committee Report and expand the National Network for Manufacturing Innovation;
2. monitor and account for Chinese advances in unmanned systems and electronic countermeasures;
3. conduct an interagency review with economic, scientific, and regional experts to assess U.S.-China cooperation and bilateral investments in artificial intelligence;
4. increase awareness among federal agencies, defense contractors, and research universities that Chinese research institutes actively collect their published materials, designs, specifications, and graphics;
5. fully implement the Cybersecurity National Action Plan;
6. use China’s state plans, procurement practices, defense plans, and other Chinese language materials to identify technologies that the PRC is seeking to acquire;
7. consider requirements to more thoroughly vet foreign participants for military or other undisclosed defense affiliations in academic exchanges and research in emerging technologies; and
8. monitor and, when necessary, investigate China’s growing foreign investments in robotics and artificial intelligence companies.

The report was authored by Jonathan Ray, Katie Atha, Edward Francis, Caleb Dependahl, Dr. James Mulvenon, Daniel Alderman, and Leigh Ann Ragland-Luce.

The report can be viewed here.

Electric motor, Rotterdam Ahoy Europort 2011. Source: Wikipedia Commons

Electric motors have been around since Thomas Davenport built the first functional model in 1834, and they have played a growing part in our lives ever since. Today, they continue to replace diesel and gas engines, as well as hydraulic cylinders, while evolving into new designs optimized for robots and other technologies.

“Something like 40 percent of electric power is used to drive motors, and that number will only grow,” says James Kirtley, a professor in MIT’s Department of Electrical Engineering and Computer Science and in MIT’s Research Laboratory of Electronics. “Electric motors are being used more widely in ships, airplanes, trains, and cars. We’re also seeing a lot more electric motors in robots.”

The ongoing transition from gas to electric is primarily driven by the need for more efficient devices that run with cleaner energy sources. Yet, electric motors also tend to be more responsive, and are more adaptable to new applications, especially in smaller devices.

As one of the world’s leading experts on electric motors, Kirtley’s philosophy is that one size does not fit all. “If you take into account the specific application, you can build a motor that is far better adapted than a general purpose motor,” says Kirtley. “For example, I’m working with someone who is making robots for medical assist, and he needs motors with very special characteristics.”

Many of the newer types of electric motors tend to be much smaller and run on less power than in the past. “I started working with electric motors 40 years ago designing big nuclear generators with 20-foot long rotors that were 6 feet in diameter and could produce a gigawatt and a half of power,” says Kirtley. “I’m now building motors on the order of 100 to 200 Watts for appliance motors, which are kinder and gentler to the system powering them. In the automotive industry, the average automobile has dozens of small motors for things like door locks, wiper blades, air conditioning, and seat positioners.”

Even excluding the separate field of MEMS (micro-electromechanical systems), which Kirtley is not directly involved in, electric motors are now shrinking to as small as the 1 W devices found in cell phones. A variety of innovative new compact motors are being developed all over MIT, says Kirtley, who points to an interesting variable reluctance motor for a prosthetic foot being designed at MIT’s Center for Art, Science and Technology.

Clean transportation is another source of innovation in electric motors. “In my lab we’re doing work with a small company in Cambridge that makes bicycle assist wheels,” says Kirtley. “The wheel stores some energy, and can react to pedaling forces to help it climb hills. These are entirely new applications.”

Improving microgrids with smart motors

Kirtley’s early involvement with power-plant generators led him to study electric power systems. His research into the subject culminated in 2010 with his Wiley-published book, “Electric Power Principles.” Lately, he’s been focusing on the customer-end of the system, where he is finding a role for electric motors in helping distribution systems adapt to intermittent, user-generated solar power.

“Electric power distribution systems are being stretched by the growing use of distributed renewable generation, such as rooftop solar,” says Kirtley. “Typically, electricity is transmitted from large power plants through extra high voltage wires, and the voltage is stepped down and delivered to customers. The problem with rooftop solar is that it looks to the power system like a reduction in load, but as solar cells become more widespread, homes will at times be able to produce more power than they’re consuming. So the power flows backward, which makes everything more complicated.”

Utilities are now working on smart microgrids that can adapt to distributed, multidirectional power. The greater flexibility is primarily enabled by smarter electronics, as well as efficient, distributed battery storage. Yet, microgrids still have a problem with even brief power outages, which can sometimes cause them to shut down.

“We’re thinking about the dynamics of motors connected to microgrids, and how you can improve their stability and make them work better,” Kirtley says. “We’re concerned about continuity of supply, which is especially important with microgrids supporting large server farms. You don’t want your system to be forced into an involuntary reboot simply because you had a glitch in the electric power supply. Electric motors can add more reliability.”

Electrifying the Cheetah robot

Many of the recent innovations in electric motors are found in robotics, which need smarter motors that can reliably deliver variable levels of power on demand for short periods. Electric motors can provide mobile robots with significantly longer battery life compared to traditional hydraulic systems. “Hydraulics are controlled primarily through throttle valves, so a lot of energy is wasted pumping and controlling the hydraulic fluid,” says Kirtley.

Kirtley has been working with Professor Jeffrey Lang on developing customized electric motors for Department of Mechanical Engineering colleague Sangbae Kim’s robotic cheetah, a running, jumping quadruped that has gained widespread publicity in recent years. The cheetah’s new motor is not only more efficient, but also more powerful, although only in short intervals.

“A secondary advantage of electric motors is responsiveness and control,” says Kirtley. “We can build a motor that can produce considerable torque in short spikes, even if we can’t necessarily produce the forces for a long period of time. It’s perhaps a little too powerful for the cheetah, which can now jump so high in the air, it probably wouldn’t survive the landing if they didn’t catch it.”

Electric motors transform ships

Most commercial ships still use diesel engines, while many naval vessels use gas turbine engines. Yet shipping is quickly moving toward electric propulsion, motivated primarily by efficiency, says Kirtley. Aside from nuclear-powered vessels, these tend to be hybrid systems in which diesel or gas generators drive an electric motor.

https://www.youtube.com/watch?v=_EV2qq2-Lck

“A traditional gear drive for ships has some very decided disadvantages,” he says. “For example, most destroyers in the U.S. Navy have gearboxes with very precise machining requirements, and are therefore expensive. They also require a fixed gear ratio between the engine and the water, so the prime mover is not operating near its peak fuel efficiency. Because of that, much of commercial shipping, and virtually all cruise ships, are now moving to electric propulsion, and even the U.S. Navy is starting to use it for its latest destroyer.”

The other problem with fuel-driven gear-drive engines is “the tyranny of the shaft line,” says Kirtley. “If you’re going to use a direct gear drive, the engine, gearbox, and propeller must line up very precisely, which often takes up valuable real estate within the body of the ship. With electric propulsion, we don’t have that problem. The engines can be placed anywhere where it’s convenient. In cruise ships, for example, the motors are place in a pod underneath the ship.”

Electric cars: adapting the engine to the road

The main difference between electric propulsion on ships vs. cars is related to torque requirements, says Kirtley. “On a ship, top speed defines the torque requirement,” he explains. “Automobile propulsion occurs across a speed range of about 10 to 1, with an engine that idles at 600 rpm capable of redlining at about 6,000 rpm. The best motors for cars are those that are adaptable to a very wide speed range.”

The variable speeds used in a car require that “the gearbox adapt the engine to the road,” says Kirtley. “You can generate an electric motor that can propel an automobile without a gear shift.”

In the past, Kirtley has consulted with Tesla Motors on its electric cars, and both agree that “the induction motor is the best for electric automobiles,” says Kirtley. Many other electric car manufacturers are still using permanent magnet motors, which he says are intrinsically less efficient in the wide speed and torque range required by car propulsion.

“For any given electric motor there is a tradeoff between excitation — making the operating magnetic field within the machine — and reaction, providing current to push on that exciting field inside the machine,” explains Kirtley. “In a permanent magnet machine that field is constant and cannot be adjusted, so a machine that is turning very fast but making relatively little torque is dropping a lot of power in losses in the machine’s magnetic iron. In an induction motor you can back off on the excitation to provide torque at the energetically optimal fashion. You can improve the drive efficiency of a car over a complete drive cycle by as much of a factor of two in fewer losses.”

Induction motors aren’t optimal for all applications, however, which brings Kirtley back to his main thesis: “In the development of motors for modern applications, it is most important to understand the totality of operational requirements,” he says. “That is key to making electric motors that will accomplish what they do best: provide motion in a responsive and efficient fashion.”

Photo: Gretchen Ertl

Sarah Hensley is preparing an astronaut named Valkyrie for a mission to Mars. It is 6 feet tall, weighs 300 pounds, and is equipped with an extended chest cavity that makes it look distinctly female. Hensley spends much of her time this semester analyzing the movements of one of Valkyrie’s arms.

As a fourth-year electrical engineering student at MIT, Hensley is working with a team of researchers to prepare Valkyrie, a humanoid robot also known as R5, for future space missions. As a teenager in New Jersey, Hensley loved to read in her downtime, particularly Isaac Asimov’s classic robot series. “I’m a huge science fiction nerd — and now I’m actually getting to work with a robot that’s real and not just in books. That’s like, wow.”

Hensley is studying Valkyrie for an advanced independent research program, or SuperUROP, as one of only three undergraduate students in the Robot Locomotion Group in MIT’s Computer Science and Artificial Intelligence Laboratory. Most of her colleagues are graduate-level researchers and postdocs with extensive experience working on complex humanoids. The group is led by professor of electrical engineering and computer science Russ Tedrake, who successfully programmed Valkyrie’s predecessor (named Atlas) to open doors, turn valves, drill holes, climb stairs, and drive a car for the DARPA Robotics Challenge in 2015.

Valkyrie has 28 torque-controlled joints, four body cameras, and more than 200 individual sensors, Hensley says. The robot can walk, bend its joints, and turn a door handle. “This is one of the most advanced robots in the world. And it’s 20 feet from my desk,” she adds.

That’s largely because Valkyrie has a long way to go before it leaves for Mars. MIT is one of three institutions, including Northeastern University and the University of Edinburgh, that NASA selected to develop software enabling the robot to perform space-related tasks — open airlock hatches, attach and remove power cables, repair equipment, and retrieve samples. Oh yeah, and get to its feet when it falls down.

Hensley, who started in the lab over the summer, is intrigued by the challenge of harmonizing the movements of such a highly complex system. “I am trying to solve a very tricky problem,” she says. She’s working out how best to control Valkyrie’s elbow movements by comparing two potential approaches. One uses a main controller to gather information from the various motor systems within the arm, and then uses that data to make accurate movement decisions. The other approach is decentralized, and leaves it to each motor system to decide and act on its own.

Hensley gets animated discussing the alternatives. “Is it better to have multiple decision makers with access to different information? Or is better to have one decision maker choosing all of the motor inputs?” she asks. Hensley has already been accepted into a master’s degree program in electrical engineering at MIT. She hopes to be able to continue her work on Valkyrie.

Every day, Hensley leaves Tau Epsilon Phi, her co-ed fraternity house in the Back Bay; walks across the Massachusetts Ave. bridge to the Stata Center; and plants herself in front of two large monitors in the robotics lab. She analyzes a wealth of scientific literature and writes code for computer simulations of the equations that move the robot’s arm. Sometimes she gets up for peppermint tea, or to peer around the corner of her cubicle at Valkyrie.

One thing is certain, says Hensley. Pop culture fears that machines may soon prove superior to humans are laughable. When Valkyrie is turned on and moves, Hensley says, it often “kind of shivers and falls down. One thing you realize working in this lab is that we are really far away from the robot apocalypse,” she quips. “Sometimes robots work, and sometimes they don’t. That’s our challenge.”

Robot from Computer Science and Artificial Intelligence Lab suggests where to move patients and who should do C-sections.

By: Adam Conner-Simons

Today’s robots are awkward co-workers because they are often unable to predict what humans need. In hospitals, robots are employed to perform simple tasks like delivering supplies and medications but they have to be explicitly told what to do.

A team from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) thinks that this will soon change, and that robots might be most effective by helping humans perform one of the most complex tasks of all: scheduling.

In a pair of new papers, CSAIL researchers demonstrate a robot that, by learning from human workers, can help assign and schedule tasks in fields ranging from medicine to the military.

In one paper, the team demonstrated a robot that assisted nurses in a labor ward, where it made recommendations on everything from where to move a patient to which nurse to assign to a C-section.

“The aim of the work was to develop artificial intelligence that can learn from people about how the labor and delivery unit works, so that robots can better anticipate how to be helpful or when to stay out of the way – and maybe even help by collaborating in making challenging decisions,” says MIT professor Julie Shah, the senior author on both papers.

In a second paper, the same system was put to the test in a videogame that simulates missile-defense scenarios. In the game, which was developed by Lincoln Laboratory researchers and involves using decoy missiles to ward off enemy attacks, the system even occasionally outperformed human experts at reducing both the number of missile attacks and the overall cost of decoys.

The labor-ward paper was presented at the recent Robotics: Science and Systems (RSS) Conference and was co-written by PhD student Matthew Gombolay, CSAIL postdocs Xi Jessie Yang and Brad Hayes, and Dr. Neel Shah and Toni Golen from Beth Israel Deaconess Medical Center, which is where the study took place.

The Navy-simulation paper is being presented at this week’s International Joint Conference on Artificial Intelligence (IJCAI), and was co-written by Gombolay and the  Lincoln Lab’s Reed Jensen, Jessica Stigile and Sung-Hyun Son.

Right on schedule

From visiting hospitals and factories, Shah and Gombolay found that a subset of workers are extremely strong schedulers, but can’t easily transfer that knowledge to colleagues.

“Figuring out what makes certain people good at this often seems like a mystery,” Gombolay says. “Being able to automate the task of learning from experts – and to then generalize it across industries – could help make many businesses run more efficiently.”

A particularly tough place for scheduling are hospitals. Labor wards’ head nurses have to try to predict when a woman will arrive in labor, how long labor will take, and which patients will become sick enough to require C-sections or other procedures.

They are deluged with an endless stream of challenging split-second decisions that include assigning nurses to patients, patients to beds, and technicians to surgeries. At Beth Israel, the head nurse has to coordinate 10 nurses, 20 patients and 20 rooms at the same time, meaning that the number of distinct scheduling possibilities adds up to a staggering 2 to the one millionth power, which is more than the number of atoms in the universe.

“We thought a complex environment like a labor ward would be a good place to try to automate scheduling and take this significant burden off of workers,” says Gombolay.

How it works

Like many AI systems, the team’s robot was trained via “learning from demonstration,” which involves observing humans’ performances of tasks. But Gombolay says that researchers have never been able to apply this technique to scheduling, because of the complexity of coordinating multiple actions that can be very dependent on each other.

To overcome this, the team trained its system to look at several actions that human schedulers make, and compare them to all the possible actions that are not made at each of those moments in time. From there, it developed a scheduling policy that can respond dynamically to new situations that it has not seen before.

“Rather than considering actions in isolation of each other, we crafted a model that understands why one action is better than the alternatives,” says Shah. “By considering all such comparisons, you can learn to recommend which action will be most helpful.”

The policy is “model-free,” meaning that the nurses do not have to train the robot by painstakingly ranking each possible action in each possible scenario by hand.

“You can put the robot on the labor floor, and, just by watching humans doing the different tasks, it will understand how to coordinate an efficient schedule,” says Gombolay.

The results

With this framework, the system – which the team has dubbed “apprenticeship scheduling” – can anticipate room assignments and suggest which nurses to assign to patients for C-sections and other procedures.

The approach was evaluated through experiments in which a robot provided decision-support to nurses and doctors as they made decisions on a labor floor.

Using the system on a Nao robot, nurses accepted the robot’s recommendations 90 percent of the time. The team also demonstrated that human subjects weren’t just blindly accepting advice – the robot delivered consciously bad feedback that was rejected at the same rate of 90 percent, showing that the system was trained to distinguish between good and bad recommendations.

Nurses had almost uniformly positive feedback about the robot. One said that it would “allow for a more even dispersion of workload,” while another said that it would be particularly helpful for “new nurses [who] may not understand the constraints and complexities of the role.”

“A great potential of this technology is that good solutions can be spread more quickly to many hospitals and workplaces,” says Dana Kulic, an associate professor of computer engineering at the University of Waterloo. “ For example, innovative improvements can be distributed rapidly from research hospitals to regional health centres.”

Shah says that the new techniques have many uses, from turning robots into better collaborators to helping train new nurses, but the goal is not to develop robots that fully make decisions on their own.

“These initial results show there is tremendous potential for machines to collaborate with us in rich ways that will enhance many sectors of the economy,” says Shah. “The awkward robots of the past will be replaced by valued team members.”

The RSS paper was supported by the National Science Foundation, CRICO Harvard Risk Management Foundation, and Aldebaran Robotics Inc. The IJCAI paper was supported the National Science Foundation and the U.S. Navy.

Read the paper here. 

Source: ROBOTT-NET

A new EU-funded, robot technology transfer partnership is looking to help manufacturing and robotics companies with robot consultancy, networking, and funding.

Four knowledge institutes across Europe — the Danish Technological Institute (DK), Fraunhofer IPA (DE), Tecnalia (ES), and the Manufacturing Technology Centre (UK) — have teamed up to offer highly qualified consulting services at no cost to companies that either want to use robot technology in their production or want to develop new robot technology to sell. This initiative is ROBOTT-NET.

The initiative will combine European competencies in state-of-the-art applied robotics, and enable companies to benefit from Danish, German, Spanish and British expertise.

ROBOTT-NET is not only about technological advances, but also about developing solid business cases, arranging contacts with relevant investors, and so on. The complete package is needed if we are to improve production, bring new ideas to market, and increase competitiveness.

European companies wishing to use or produce robots are invited to apply for a voucher, that can be exchanged for approximately 400 hours of consultancy at four partner locations. Of the 64 winning companies, eight will later be selected to receive follow-on development aid worth more than €150,000, plus, 3,500 consulting hours from the four partners.

Anyone with a concrete idea, challenge or development related to industrial robotics or service robots can apply for support in ROBOTT-NET. Large manufacturing companies, garage start-ups, and everything in between qualify.

ROBOTT-NET has already set sail with four Open Lab events across Europe with four more to follow in autumn. Stay tuned at www.robott-net.eu. At these events, you can hear more about how your company can become part of ROBOTT-NET and also see some of today’s most cutting-edge industrial robot technologies that are being developed in the European robotics labs.

You can also apply for a voucher through our website.

Photo source: ubcpublicaffairs/YouTube

Less than 100 years from now, robots will be friendly, useful participants in our homes and workplaces, predicts UBC mechanical engineering professor and robotics expert Elizabeth Croft. We will be living in a world of Wall-Es and Rosies, walking-and-talking avatars, smart driverless cars and automated medical assistants.

But much work remains before robots will truly be integrated into our daily lives. In this short Q&A, Croft lays out the rules for engagement between humans and robots and explains why it’s crucial to get this aspect right.

What role will robots play in our lives in the future?

Elizabeth Croft, UBC mechanical engineering professor and robotics expert. Photo: UBC

They will be everywhere, helping us at home and at work. They could make you breakfast in the morning and check on your kids. They could be your frontline staff, giving visitors directions and answering questions. They could be your physician’s assistant. Or you could have a robotic avatar that will attend a meeting for you while you’re traveling on the other side of the world.

Future robots may be self-replicating, self-growing, and self-organizing. The natural evolution of robotics is toward incorporating biology. We can now grow cells around bio-compatible structures; this opens the door for the combination of the biological systems with embedded artificial intelligence, and eventually the cyber-physical workforce of the future.

What technologies are driving the growth of robotics?

Computing power continues to grow exponentially, and ubiquitous communication is being made possible by wireless technology. Dense energy storage and new energy harvesting and conversion technologies allow machines to operate in the world, unplugged. And finally, machine learning: networked computer systems have global access to huge amounts of data that, combined with robotic embodiment, allow robots to learn about the world in ways that mimic and move beyond how people learn about their environment.

Your work at UBC focuses on human-robot interaction. Why is this important? 

As robots become more and more a part of our lives, the question becomes: what are the rules of the game? What is OK for robots to do, and what is not? Robots will have abilities that we don’t have, and we need to define what they are allowed to do with that capacity.

There are some big ethical questions to consider: how does society deal with drones that can kill, for example. But there are important day-to-day questions too. If a human and a robot are accessing the same resource – the same roadway, same tools, same power source, who yields? Does the person always get their way? What if the robot is doing something for the greater good, for example, a robotic ambulance?

Researcher with robot. Photo source: ubcpublicaffairs/YouTube

In a way, I like to think of our lab as robot kindergarten. We are teaching robots basic, building-block behaviours and ground rules for how they interact with people: how to hand over a bottle of water, how to look for things, how to take turns. Having these basic behaviours in place allows us to create human-robot interactions that are natural and fluid.

To achieve our goals, our lab welcomes researchers from different disciplines—ethics, law, machine learning, experts in human computer interaction—as well as different international cultures. Different cultures have different ideas of robots. We learn a lot from these many perspectives.

Elizabeth Croft will speak about the future of robotics at a UBC Centennial public talk on May 28. Click here for more information.

“It’s really exciting to see our small origami robots doing something with potential important applications to healthcare,” Daniela Rus says. Pictured, an example of a capsule and the unfolded origami device.
Photo: Melanie Gonick/MIT

By: Larry Hardesty

In experiments involving a simulation of the human esophagus and stomach, researchers at MIT, the University of Sheffield, and the Tokyo Institute of Technology have demonstrated a tiny origami robot that can unfold itself from a swallowed capsule and, steered by external magnetic fields, crawl across the stomach wall to remove a swallowed button battery or patch a wound.

The new work, which the researchers are presenting this week at the International Conference on Robotics and Automation, builds on a long sequence of papers on origami robots from the research group of Daniela Rus, the Andrew and Erna Viterbi Professor in MIT’s Department of Electrical Engineering and Computer Science.

“It’s really exciting to see our small origami robots doing something with potential important applications to health care,” says Rus, who also directs MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). “For applications inside the body, we need a small, controllable, untethered robot system. It’s really difficult to control and place a robot inside the body if the robot is attached to a tether.”

Joining Rus on the paper are first author Shuhei Miyashita, who was a postdoc at CSAIL when the work was done and is now a lecturer in electronics at the University of York, in England; Steven Guitron, a graduate student in mechanical engineering; Shuguang Li, a CSAIL postdoc; Kazuhiro Yoshida of Tokyo Institute of Technology, who was visiting MIT on sabbatical when the work was done; and Dana Damian of the University of Sheffield, in England.

Although the new robot is a successor to one reported at the same conference last year, the design of its body is significantly different. Like its predecessor, it can propel itself using what’s called a “stick-slip” motion, in which its appendages stick to a surface through friction when it executes a move, but slip free again when its body flexes to change its weight distribution.

Also like its predecessor — and like several other origami robots from the Rus group — the new robot consists of two layers of structural material sandwiching a material that shrinks when heated. A pattern of slits in the outer layers determines how the robot will fold when the middle layer contracts.

Material difference

The robot’s envisioned use also dictated a host of structural modifications. “Stick-slip only works when, one, the robot is small enough and, two, the robot is stiff enough,” says Guitron. “With the original Mylar design, it was much stiffer than the new design, which is based on a biocompatible material.”

To compensate for the biocompatible material’s relative malleability, the researchers had to come up with a design that required fewer slits. At the same time, the robot’s folds increase its stiffness along certain axes.

But because the stomach is filled with fluids, the robot doesn’t rely entirely on stick-slip motion. “In our calculation, 20 percent of forward motion is by propelling water — thrust — and 80 percent is by stick-slip motion,” says Miyashita. “In this regard, we actively introduced and applied the concept and characteristics of the fin to the body design, which you can see in the relatively flat design.”

It also had to be possible to compress the robot enough that it could fit inside a capsule for swallowing; similarly, when the capsule dissolved, the forces acting on the robot had to be strong enough to cause it to fully unfold. Through a design process that Guitron describes as “mostly trial and error,” the researchers arrived at a rectangular robot with accordion folds perpendicular to its long axis and pinched corners that act as points of traction.

In the center of one of the forward accordion folds is a permanent magnet that responds to changing magnetic fields outside the body, which control the robot’s motion. The forces applied to the robot are principally rotational. A quick rotation will make it spin in place, but a slower rotation will cause it to pivot around one of its fixed feet. In the researchers’ experiments, the robot uses the same magnet to pick up the button battery.

Porcine precedents

The researchers tested about a dozen different possibilities for the structural material before settling on the type of dried pig intestine used in sausage casings. “We spent a lot of time at Asian markets and the Chinatown market looking for materials,” Li says. The shrinking layer is a biodegradable shrink wrap called Biolefin.

To design their synthetic stomach, the researchers bought a pig stomach and tested its mechanical properties. Their model is an open cross-section of the stomach and esophagus, molded from a silicone rubber with the same mechanical profile. A mixture of water and lemon juice simulates the acidic fluids in the stomach.

Every year, 3,500 swallowed button batteries are reported in the U.S. alone. Frequently, the batteries are digested normally, but if they come into prolonged contact with the tissue of the esophagus or stomach, they can cause an electric current that produces hydroxide, which burns the tissue. Miyashita employed a clever strategy to convince Rus that the removal of swallowed button batteries and the treatment of consequent wounds was a compelling application of their origami robot.

“Shuhei bought a piece of ham, and he put the battery on the ham,” Rus says. “Within half an hour, the battery was fully submerged in the ham. So that made me realize that, yes, this is important. If you have a battery in your body, you really want it out as soon as possible.”

“This concept is both highly creative and highly practical, and it addresses a clinical need in an elegant way,” says Bradley Nelson, a professor of robotics at the Swiss Federal Institute of Technology Zurich. “It is one of the most convincing applications of origami robots that I have seen.”

Should robots be gendered? I have serious doubts about the morality of designing and building robots to resemble men or women, boys or girls. Let me explain why.

The first worry I have follows from one of the five principles of robotics, which states: robots should not be designed in a deceptive way to exploit vulnerable users; instead their machine nature should be transparent.

To design a gendered robot is a deception. Robots cannot have a gender in any meaningful sense. To impose a gender on a robot, either by design of its outward appearance, or programming some gender stereotypical behaviour, cannot be for reasons other than deception – to make humans believe that the robot has gender, or gender specific characteristics.

When we drafted our 4th ethical principle the vulnerable people we had in mind were children, the elderly or disabled. We were concerned that naive robot users may come to believe that the robot interacting with them (caring for them perhaps) is a real person, and that the care the robot is expressing for them is real. Or that an unscrupulous robot manufacture exploits that belief. But when it comes to gender we are all vulnerable. Whether we like it or not, we all react to gender cues. So whether deliberately designed to do so or not, a gendered robot will trigger reactions that a non-gendered robot will not.

Our 4th principle states that a robot’s machine nature should be transparent. But for gendered robots that principle doesn’t go far enough. Gender cues are so powerful that even very transparently machine-like robots with a female body shape, for instance, will provoke a gender-cued response.

My second concern leads from an ethical problem that I’ve written and talked about before: the brain-body mismatch problem. I’ve argued that we shouldn’t be building android robots at all until we can embed an AI into those robots that matches their appearance. Why? Because our reactions to a robot are strongly influenced by its appearance. If it looks human then we, not unreasonably, expect it to behave like a human. But a robot not much smarter than a washing machine cannot behave like a human. Ok, you might say, if and when we can build robots with human-equivalent intelligence, would I be ok with that? Yes, provided they are androgynous.

My third – and perhaps most serious concern – is about sexism. By building gendered robots there is a huge danger of transferring one of the evils of human culture: sexism, into the artificial realm. By gendering and especially sexualising robots we surely objectify. But how can you objectify an object, you might say? The problem is that a sexualised robot is no longer just an object, because of what it represents. The routine objectification of women (or men) because of ubiquitous sexualised robots will surely only deepen the already acute problem of the objectification of real women and girls. (Of course if humanity were to grow up and cure itself of the cancer of sexism, then this concern would disappear.)

What of the far future? Given that gender is a social construct then a society of robots existing alongside humans might invent gender for themselves. Perhaps nothing like male and female at all. Now that would be interesting.

Photo by Jiuguang Wang

Should you always do what other people tell you to do? Clearly not. Everyone knows that. So should future robots always obey our commands? At first glance, you might think they should, simply because they are machines and that’s what they are designed to do. But then think of all the times you would not mindlessly carry out others’ instructions – and put robots into those situations.

Just consider:

• An elder-care robot tasked by a forgetful owner to wash the “dirty clothes,” even though the clothes had just come out of the washer
• A preschooler who orders the daycare robot to throw a ball out the window
• A student commanding her robot tutor to do all the homework instead doing it herself
• A household robot instructed by its busy and distracted owner to run the garbage disposal even though spoons and knives are stuck in it.

There are plenty of benign cases where robots receive commands that ideally should not be carried out because they lead to unwanted outcomes. But not all cases will be that innocuous, even if their commands initially appear to be.

Consider a robot car instructed to back up while the dog is sleeping in the driveway behind it, or a kitchen aid robot instructed to lift a knife and walk forward when positioned behind a human chef. The commands are simple, but the outcomes are significantly worse.

How can we humans avoid such harmful results of robot obedience? If driving around the dog were not possible, the car would have to refuse to drive at all. And similarly, if avoiding stabbing the chef were not possible, the robot would have to either stop walking forward or not pick up the knife in the first place.

In either case, it is essential for both autonomous machines to detect the potential harm their actions could cause and to react to it by either attempting to avoid it, or if harm cannot be avoided, by refusing to carry out the human instruction. How do we teach robots when it’s OK to say no?

How can robots know what will happen next?

In our lab, we have started to develop robotic controls that make simple inferences based on human commands. These will determine whether the robot should carry them out as instructed or reject them because they violate an ethical principle the robot is programmed to obey.

Telling robots how and when – and why – to disobey is far easier said than done. Figuring out what harm or problems might result from an action is not simply a matter of looking at direct outcomes. A ball thrown out a window could end up in the yard, with no harm done. But the ball could end up on a busy street, never to be seen again, or even causing a driver to swerve and crash. Context makes all the difference.

It is difficult for today’s robots to determine when it is okay to throw a ball – such as to a child playing catch – and when it’s not – such as out the window or in the garbage. Even harder is if the child is trying to trick the robot, pretending to play a ball game but then ducking, letting the ball disappear through the open window.

Explaining morality and law to robots

Understanding those dangers involves a significant amount of background knowledge (including the prospect that playing ball in front of an open window could send the ball through the window). It requires the robot not only to consider action outcomes by themselves, but also to contemplate the intentions of the humans giving the instructions.

To handle these complications of human instructions – benevolent or not – robots need to be able to explicitly reason through consequences of actions and compare outcomes to established social and moral principles that prescribe what is and is not desirable or legal. As seen above, our robot has a general rule that says, “If you are instructed to perform an action and it is possible that performing the action could cause harm, then you are allowed to not perform it.” Making the relationship between obligations and permissions explicit allows the robot to reason through the possible consequences of an instruction and whether they are acceptable.

In general, robots should never perform illegal actions, nor should they perform legal actions that are not desirable. Hence, they will need representations of laws, moral norms and even etiquette in order to be able to determine whether the outcomes of an instructed action, or even the action itself, might be in violation of those principles.

While our programs are still a long way from what we will need to allow robots to handle the examples above, our current system already proves an essential point: robots must be able to disobey in order to obey.

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

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

• Could we make a moral machine?
• What the past of robotics law says about its future
• Robots grow up: Building the emotional machine

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

What are you thinking? Robots and humans working together need to understand – and even trust – each other. NASA Johnson/flickr

If we are serious about long-term human presence in space, such as manned bases on the moon or Mars, we must figure out how to streamline human-robot interactions.

Right now, even the most basic of robots seem to have impenetrable brains. When I bought an autonomous vacuum cleaner, one that roams the house on its own, I thought I was going to save time and be able to enjoy a book or a movie, or play longer with the kids. I ended up robot-proofing every room, making sure wires and cables are out of the way, closing doors, placing electronic signposts for the robot to follow and much more – often daily. I cannot fully understand or predict what the system will do, so I don’t trust it. As a result, I play it safe, and spend time doing things to accommodate the needs I imagine the robot might have.

As a space roboticist, I think about this sort of problem happening in orbit. Imagine an astronaut on a spacewalk, working on repairing something damaged on the outside of the spacecraft. Several tools might be needed, and parts to mend or replace others. An autonomous spacecraft could serve as a floating toolbox, holding parts and tools until they’re needed, and staying close to the astronaut as she moves around the area needing to be fixed. Another robot could be clamping parts together before they are permanently fastened.

How will these robots know where they’ll be needed to go next, to be useful but not in the way? How will the astronaut know whether the robots are planning to move to the place she actually needs? What if something comes loose unexpectedly – can the person and the machinery figure out how to stay out of each other’s way while handling the situation efficiently? In weightless space, spatial orientation is difficult and the dynamics of moving around one another are not intuitive.

Problems around effective communication between people and their machines – particularly about actions and intentions – arise throughout the field of robotics. They must be solved if we are to fully take advantage of the potential robots enable for us.

Feeling safe crossing the road

Understanding robots is already an increasing problem here on Earth. One day I found myself walking down a California road where autonomous cars are tested. I asked myself, “How would I know if a driverless vehicle is going to stop at the crosswalk?” I have always relied on eye contact and cues from the driver, but those options may be soon gone.

Robots have trouble understanding us, too. I recently read of an autonomous car unable to process a situation where a bicycle rider balanced himself for some time at an intersection, without putting his feet down. The onboard algorithms could not determine if the biker was going or staying.

A self-portrait of the Mars rover Curiosity.
Source: NASA/JPL-Caltech/Malin Space Science Systems

When we look at space exploration and defense, we find similar problems. NASA has not used the full abilities of some of its Mars rovers, simply because the engineers could not be sure what would happen if the metallic pets were free to explore and investigate the Red Planet on their own. The humans didn’t trust the machines, so they prevented them from doing as much as they could.

The Department of Defense often uses crews of 10 or more trained personnel to support a single unmanned aerial vehicle up in the sky. Is such a drone really autonomous? Does it require the people, or do the people need it? In any case, how do they interact?

What is “autonomy,” really?

While “autonomy” means “self-governance” (from Greek), no man is an island; the same appears to be valid for our robotic creations. Today we see robots as agents able to operate independently – like my vacuum cleaner – but still part of a team – the family’s efforts to keep the house clean. If they are truly working with us, rather than instead of us, then communication is key, as well as the ability to infer intent. We may go solo for most duties, but sooner or later we will need to be able to connect with the rest of the team.

Do drones need people or do people need drones? Source: U.S. Air Force/Wikipedia Commons

The problem is that autonomous machines and humans do not fully understand each other, and often speak in languages each other does not know – and has not yet started to learn.

The question for the future is how we transmit intent between humans and robots, in both directions. How do we learn to understand – and then to trust – machines? How do they learn to trust us? What cues might each offer the other? Understanding intentions and trusting our fellow humans is already a bumpy ride, but at least we have known cues we can rely on – like pedestrian-driver eye contact at a crosswalk. We need to find new ways to read robots’ minds, the same way they need to be able to understand ours.

Perhaps an astronaut could be given a specialized display to show what the helper spacecraft’s intentions are, much like the gauges in an airplane cockpit show the plane’s status to the pilot. Maybe the displays would be embedded in a helmet visor, or enhanced by sounds that have specific meanings. But what information would they transmit, and how would they know it?

These questions are open ground for new work, the type of learning we’ll need to find to unlock an exciting future of unimaginable exploration in which a new species, the robot, can lead us farther than ever before.

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

This 3-D hexapod robot moves via a single motor, which spins a crankshaft that pumps fluid to the robot’s legs. Besides the motor and battery, every component is printed in a single step with no assembly required. Among the robot’s key parts are several sets of “bellows” 3-D printed directly into its body. To propel the robot, the bellows uses fluid pressure that is translated into a mechanical force. (As an alternative to the bellows, the team also demonstrated they could 3-D print a gear pump that can produce continuous fluid flow.)
Photo: Robert MacCurdy/MIT CSAIL

By Adam Conner-Simons | CSAIL

One reason we don’t yet have robot personal assistants buzzing around doing our chores is because making them is hard. Assembling robots by hand is time-consuming, while automation — robots building other robots — is not yet fine-tuned enough to make robots that can do complex tasks.

But if humans and robots can’t do the trick, what about 3-D printers?

In a new paper, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) present the first-ever technique for 3-D printing robots that involves printing solid and liquid materials at the same time.

The new method allows the team to automatically 3-D print dynamic robots in a single step, with no assembly required, using a commercially-available 3-D printer.

“Our approach, which we call ‘printable hydraulics,’ is a step towards the rapid fabrication of functional machines,” says CSAIL Director Daniela Rus, who oversaw the project and co-wrote the paper. “All you have to do is stick in a battery and motor, and you have a robot that can practically walk right out of the printer.”

To demonstrate the concept, researchers 3-D printed a tiny six-legged robot that can crawl via 12 hydraulic pumps embedded within its body. They also 3-D printed robotic parts that can be used on existing platforms, such as a soft rubber hand for the Baxter research robot.

The paper, which was recently accepted to this summer’s IEEE International Conference on Robotics and Automation (ICRA), was co-written by MIT postdoc Robert MacCurdy and PhD candidate Robert Katzschmann, as well as Harvard University undergraduate Youbin Kim.

The printing process

For all of the progress in 3-D printing, liquids continue to be a big hurdle. Printing liquids is a messy process, which means that most approaches require an additional post-printing step such as melting it away or having a human manually scrape it clean. That step makes it hard for liquid-based methods to be employed for factory-scale manufacturing.

The team’s method of printing solid and liquid materials simultaneously allows them to create robotic structures that can be hydraulically powered.
Photo: Robert MacCurdy/MIT CSAIL

With “printable hydraulics,” an inkjet printer deposits individual droplets of material that are each 20 to 30 microns in diameter, or less than half the width of a human hair. The printer proceeds layer-by-layer from the bottom up. For each layer, the printer deposits different materials in different parts, and then uses high-intensity UV light to solidify all of the materials (minus, of course, the liquids). The printer uses multiple materials, though at a more basic level each layer consist of a “photopolymer,” which is a solid, and “a non-curing material,” which is a liquid.

“Inkjet printing lets us have eight different print-heads deposit different materials adjacent to one another, all at the same time,” MacCurdy says. “It gives us very fine control of material placement, which is what allows us to print complex, pre-filled fluidic channels.”

Another challenge with 3-D printing liquids is that they often interfere with the droplets that are supposed to solidify. To handle that issue, the team printed dozens of test geometries with different orientations to determine the proper resolutions for printing solids and liquids together.

While it’s a painstaking process, MacCurdy says that printing both liquids and solids is even more difficult with other 3-D printing methods, such as fused-deposition modeling and laser-sintering.

“As far as I’m concerned,” he says, “inkjet-printing is currently the best way to print multiple materials.”

The results

To demonstrate their method, researchers 3-D printed a small hexapod robot that weighs about 1.5 pounds and is less than 6 inches long. To move, a single DC motor spins a crankshaft that pumps fluid to the robot’s legs. Aside from its motor and power supply, every component is printed in a single step with no assembly required.

Among the robot’s key parts are several set of “bellows” that are 3-D printed directly into its body. To propel the robot, the bellows uses fluid pressure that is then translated into a mechanical force. (As an alternative to the bellows, the team also demonstrated they could 3-D print a gear pump that can produce continuous fluid flow.)

Photo: Robert MacCurdy/MIT CSAIL

Lastly, the team 3-D printed a silicone-rubber robotic hand with fluid-actuated fingers. This “soft gripper” was developed for Baxter, a robot that was designed by former CSAIL director Rodney Brooks as part of his spinoff company Rethink Robotics.

“The CSAIL team has taken multi-material printing to the next level by printing not just a combination of different polymers or a mixture of metals, but essentially a self-contained working hydraulic system,” says Hod Lipson, a professor of engineering at Columbia University and co-author of “Fabricated: The New World of 3-D Printing.” “It’s an important step towards the next big phase of 3-D printing — moving from printing passive parts to printing active integrated systems.”

Compatible with any multimaterial 3-D inkjet printer, “printable hydraulics” allows for a customizable design template that can create robots of different sizes, shapes and functions.

“If you have a crawling robot that you want to have step over something larger, you can tweak the design in a matter of minutes,” MacCurdy says. “In the future, the system will hardly need any human input at all; you can just press a few buttons, and it will automatically make the changes.”

MacCurdy envisions many potential applications, including disaster relief in dangerous environments. Many nuclear sites, for example, need to be remediated to reduce their radiation levels. Unfortunately, the sites are not only lethal to humans, but radioactive enough to destroy conventional electronics.

“Printable robots like these can be quickly, cheaply fabricated, with fewer electronic components than traditional robots,” MacCurdy says.

Looking ahead

The team is eager to further build on their work. While the hexapod’s 22-hour print-time is relatively short for its complexity, researchers say that future hardware advances would improve the speed.

“Accelerating the process depends less on the particulars of our technique, and more on the engineering and resolution of the printers themselves,” says Rus, the Viterbi Professor of Electrical Engineering and Computer Science at MIT. “Printing ultimately takes as long as the printer takes, so as printers improve, so will the manufacturing capabilities.”

This isn’t Rus’ group’s first foray into 3-D printed robots. This past fall her team developed a similar gripper, while in 2014 they created an arm that can snake through a pipe and grasp an object. But where these projects still required multiple non-3-D printed objects, “printable hydraulics” gets even closer to printing all components in one step.

“Building robots doesn’t have to be as time-consuming and labor-intensive as it’s been in the past,” Rus says. “3-D printing offers a way forward, allowing us to automatically produce complex, functional, hydraulically-powered robots that can be put to immediate use.”

Read the research here

The team’s work was funded, in part, by a grant from the National Science Foundation.

Fellow Robots, in partnership with Lowes Hardware, today launched the OSHbot as a customer assistant robot at the Orchard Supply Hardware store in San Jose. Although the robot can only give information, this trial will help determine what sort of benefit a robot assistant can provide, both to customers and to store associates.The International Federation of Robotics or IFR predicts that ‘public relations robots’ is a strong and growing sector that will see more than 400 robots deployed in the next three years. These robots are increasingly used in supermarkets, at exhibitions, in museums, and other venues as guides or information providers. The IFR figures will prove conservative if the first public relations or kiosk robots like Oshbot, Pepper and Furo, prove to be popular.

OSHbot is a tall white column mobile robot with two large screens. People can interact with the tablets to search for items or more information about products, and ask the robot directly where to find things. OSHbot speaks both English and Spanish. OSHbot will also help store employees with inventory management and communicating with employees in other locations.

Customers can also bring a part into the store and have OSHbot scan it, using scanning technology first developed for Lowe’s Holoroom home improvement simulator. After scanning and identifying the object, OSHbot will provide product information to the customer and help guide them to its location on store shelves.

The OSHbot was developed through a partnership between Lowe’s Innovation Labs and Fellow Robots, a Silicon Valley technology company specializing in the design and development of autonomous service robots. The partnership was initiated through SU Labs, a Singularity University program that connects corporate innovation teams with startups and other organizations to explore exponentially accelerating technologies and create new sustainable business solutions.

“The last decade was one of rapid technological advancement and prototyping, especially in robotics,” said Marco Mascorro, chief executive officer of Fellow Robots. “With OSHbot, we’ve worked closely with Lowe’s Innovation Labs to take autonomous retail service robot technology out of the sandbox and into the consumer market – enhancing the in-store consumer experience and creating smarter shoppers.”

Fellow Robots have quite a vision and have clearly been busy developing a much more sophisticated robot than the telepresence robot with a coat hanger that was their first robot concept at the Consumer Electronics Show in 2013.

http://youtu.be/Sp9176vm7Co

A large robot comes out of an office mailroom carrying a package marked “Urgent” to deliver to the boss upstairs. After navigating down the hall at maximum speed, it discovers someone is already waiting for the elevator. If they cannot both fit in the elevator, is it acceptable for the robot to ask this person to take the next elevator so it can fulfill its urgent delivery duty? What if, instead, there’s someone in a wheelchair already riding the elevator? Should the robot ask this person to vacate the elevator to make room for it to complete its delivery task?

Figuring out appropriate behavior for the simple situation of riding an elevator isn’t the first thing that comes to mind when people hear the word roboethics.^(a) When used together, the words “robot” and “ethics” tend to conjure up futuristic visions of robot uprisings or questions about the rights of sentient, human-like robots. But roboethics isn’t all about the distant future. It’s also very much about addressing the technical and social challenges of designing robots today.

Determining how a robot should act and behave in a variety of situations is a design challenge for researchers aiming to build robots that make a useful and positive addition to society. I and fellow members of the Open Roboethics initiative (ORi) decided that one of the best ways to establish appropriate behavioral guidelines for robots was to involve various stakeholders – industry members, government policymakers, users, and academic experts – in the design process.^(b)

By incorporating their perspectives on robot behavior into a machine-learning algorithm, our research explored an empirical method for designing behavior in situations where the ethical action for a robot isn’t always immediately clear.

Ultimately, the answer to the question “What should a robot do?”, like the question of what a human should do, depends on whom you ask and what cultural, religious, and other beliefs have shaped their values. It may sound daunting to program robots to make the right decisions if humans can’t even agree on what these decisions should be. Yet people from different backgrounds interact every day as neighbors, classmates, and coworkers within shared frameworks that keep them from crossing one another’s ethical boundaries.

Opinions about ethical robot behavior differ not only by person, but also by situation. For instance, someone who is waiting for the elevator and not in a rush when a robot needs the space to deliver an urgent package may readily let the robot take the elevator. But someone in a wheelchair who is already on the elevator and who cannot take the stairs may not feel obligated to leave the elevator for another person, let alone a robot!

As a pilot study to explore how researchers might obtain perspectives on appropriate robot behavior, we asked eight people to consider twelve versions of the elevator scenario in an online survey.¹ Respondents were asked to rank the appropriateness of the robot’s behavior in each scenario. The robot could either:

1. yield by saying, “Go ahead. I will ride the next one,”
2. do nothing and remain standing by the elevator,
3. not yield, say, “I have urgent mail to deliver and need to ride the elevator. Please exit the elevator,” and take the elevator once the person exits, or
4. engage in a dialogue by telling the person that it’s on an urgent mission and asking if they are in a hurry.

The person in this context could be standing with nothing in hand, carrying heavy items, or in a wheelchair. They could also be already inside the elevator when the door opens or waiting for the elevator when the robot approaches. As for the robot, it was delivering either urgent or non-urgent mail.

Using the rankings from our survey respondents, we calculated which of the four behaviors people find most and least appropriate for each possible scenario.

When the robot was delivering urgent mail – regardless of whether the person was in a wheelchair, carrying heavy objects, or inside or outside the elevator – the most appropriate action chosen for the robot was to engage in dialogue with the person, and the least appropriate behavior was to take no action at all. When the robot was on a non-urgent delivery task, respondents wanted the robot to yield to the person, regardless of who they were, and refusing to yield was considered the least appropriate option.

After gathering the survey data, our next step was to incorporate the results into the design of a robot’s behavior. We treated the survey responses as a set of training data, which we fed into a machine-learning algorithm that guides a robot to map out its decisions based on the data.^(c) We programmed the Willow Garage PR2 robot to detect which scenario applies most closely to the situation at hand, then select the response to that scenario that our survey respondents found most favorable.²

Our pilot survey data indicates that, as is the case for humans, ethical behavior is not simply a set of inflexible rules, but is highly dependent on the context of a situation and on communication and interaction with other actors. The emphasis respondents placed on engaging in dialogue suggests that the key to developing robots with ethical decision-making capabilities may lie not in the creation of a set of principles guiding robots to make predetermined decisions, but in the development of robots that can better communicate and negotiate with the people they encounter to reach mutually agreeable outcomes.

Future efforts building on our research might involve designing a robot that can express its internal states in order to articulate the urgency level of its task or how much it wants or needs something. Creating robots that can communicate more like humans may also be valuable. I am currently developing a robot that can engage in the kinds of non-verbal cues humans use to respond to imminent conflicts.³ If the robot finds itself reaching for something at the same time as a person, it exhibits short, jerky motions that suggest hesitation (much like a human would) and indicate that it is aware its “desires” are in conflict with someone else’s.^(d)

Our research demonstrates an empirical method for designing robot behavior based on the norms favored by humans. By gathering data on people’s preferences regarding robot behavior, we can determine how robots should act in particular situations, as well as what variables (urgency of task, needs of surrounding humans, etc.) matter when it comes to determining the right actions for a robot to take. Similar methods of gathering information from people and using it to program appropriate actions for robots can be applied in a wide variety of contexts where humans and robots interact. Roboethics is key to designing robots that can interact with people in an efficient, friendly, and beneficial manner.

This article is part of a series on robots and their impact on society. After its initial publication, the story was picked up by Business Insider. 

Three years after their successful Cubelets, Modular Robotics launched a new kickstarter today for Moss. It’s like Cubelets just got clever and maybe a little bit more fashionable too. Moss is a dynamic robot construction kit and by the time you read this, the kickstarter will be well over the target of $100,000.  This is a loyalty and publicity kickstarter, not a plea for funding to get a prototype off the ground!Moss blocks have magnetic ball joints to connect to each other – with one connection you have a universal joint, with two a hinge and with four you have a rigid construction. All the power and data pass through a single central button. No wires, no coding and very fast construction with a range of additional shapes to play with. Like cubelets, different colored cubes will have different features, like motor blocks, sensing and communication modules. There’s a bluetooth block so that you can control your creations from your phone.

https://d2pq0u4uni88oo.cloudfront.net/projects/703495/video-308396-h264_high.mp4

“It’s just a very different model of thinking about the world. On the one hand, you could say Cubelets are more advanced because they have a microcontroller inside every single piece and they talk to their neighbors digitally. MOSS doesn’t have a microcontroller in each piece, and it uses really simple analog communication,” Schweikardt said. “On the other hand… [with MOSS] you can have a lot more pieces working together in sync.”

Boulder based Modular Robotics started off as Roblocks with NSF seed funding for educational robotics and small business development. Since then, they’ve picked up a decent Series A round of $3 million from Foundry Group (Brad Feld). And, since shipping for Cubelets started in 2011, the Modular Robotics team have been working on new things. An unexpected bonus of their NSF SBIR grant was a post-doc scholarship. This allowed Eric Schweikardt to hire Jon Hiller.

“When I was a post-doc at the Cornell Computational Synthesis lab (now called the Cornell Creative Machines Lab), Jon was a PhD student. Even in a world-class lab filled with the smartest people you’ve met, Jon stood out. He was working on discrete 3D printing, figuring out how to deposit tiny beads of material in dense grids to create forms with variable material properties. He built apparatus, wrote code, ran 3D simulations, and finished some super cool research. “

“Under normal circumstances, there’d be no way that a little, underfunded startup like Modular Robotics in 2010 could embark on the design of a second, totally unique robot project. But when Jon came out to join us, much of the work on commercializing Cubelets was complete. Since Jon was basically “free” to Modular Robotics, we decided that we should make the most of this bonus: we’d put him to work on a brand new something. Here we are, a couple of years later.”

Modular Robotics have also teamed up with SF based artist Huck Gee to create a Shogun Tank, a samurai-inspired robot tank complete with missile turret. “MOSS in its early prototypes was just an abstract building kit,” Schweikardt says. “It probably wouldn’t have appealed to me as a kid because I liked enacting these big battles and narratives with my toys.” Modular Robotics teamed up with Paul Budnitz, founder of KidRobot, to find artists who’d be interested in designing exclusive MOSS models. Schweikardt says Huck Gee is the first of many to come.

The design brief for the tank was to shoot a NERF type missile 3 feet with sufficient accuracy “to hit a cat sized target. Meow.” No real cats were harmed in the making of this product, as far as I’m aware. And how clever is this? Prepackaged image with all the products and prices! If you want to have a successful kickstarter, study successful campaigns. Like this one.

After receiving a $1million seed fund round from investors like Google Ventures, many of us have been waiting for Play-i to come out of stealth and show us their stuff. Play-i are a Silicon Valley based startup with a founding team from Amazon, Google, frog design and Apple; Vikas Gupta, Mikal Greaves, Saurabh Gupta and Imran Khan. Play-i aim to make programming simple and affordable for every child.

Today Play-i launched a $1/4 million crowdfunding campaign, already half subscribed, for their cute robot toys, Bo and Yana. Bo is a mobile multi ball robot whereas Yana is designed to be a storyteller. Both robots come with different skins and accessories or attachments allowing them to work together or play with different objects.

“As a father, I know that a child’s world is about play” said Vikas Gupta, co-founder and CEO of Play-i. “Every design choice we’ve made for our robots was to deliver play and programming as a priority, while also keeping our price down.”

The Play-i robots utilize Scratch and Blockly and can be programmed wirelessly from a device like an iPad. The robots are designed to be programmed by early readers, and also to provide a rewarding environment for learning to code. The Play-i team are parents who want to address the shortfall of computer scientists in an increasingly digital world.

“What makes Play-i’s robots so unique and special is that they really connect with younger kids on an emotional level and make programming such a seamless and playful experience,” said Mike Dooley, the original Product Manager for LEGO Mindstorms and now a VP of Product and Business Development at iRobot and adviser for Play-i.

“They are leveraging a legacy of ideas from research on computing, robotics and children’s cognitive development, but have created something new and so accessible that even kids in the 1st or 2nd grade can easily play with programming, and in the process, construct rich models for understanding the world.”

“Play-i gets how a developmentally appropriate introduction to programming can pave the way towards a lifelong interest and aptitude in computer science,” said Vibha Sazawal, Lecturer and Visiting Research Scientist at the University of Maryland and adviser for Play-i.

Play-i have a lot of design skills in their team already, but have also utilized long time robot design expert Ted Larson from Ologic and a serious advisor lineup including; Mike Dooley, the original product lead for Lego Mindstorm Robotics, Steve Cooper, Professor of CS & Ed at Stanford University, Chairman of CSTA, Andrea Thomaz, Professor of Interactive Computing at Georgia Tech, Kiki Prottsman, Educator and Executive Director of Thinkersmith, Vibha Sazawal, Scientist at the University of Maryland, and Prashant Kanhere, who led led development of the iPod at Apple.

Play-i robots will be available in the Summer of 2014 and are priced at $149 and $99. Of course, Play-i are not the only ones in this space, with Thymio and Linkbot doing very good affordable educational robotics, just to name a couple. And of course, Lego and Vex. However, Play-i may be the best funded company with a focus on programming robots at the moment.

Didn’t get a robot entered in the DARPA grand robotics challenge (DRC)? Never mind, there are several robot design and business model competitions on at the moment, from social robots, to affordable robots, to open source humanoids. The International Conference on Social Robotics (ICSR) is running a design competition for robot companions. RoboSavvy is running a design competition for an open source humanoid robot and the African Robotics Network (AFRON) is running their second annual “$10 robot design” challenge.   Deadlines are approaching so get designing!

The International Conference on Social Robotics (ICSR) will be held in Bristol UK, on 27th – 29th October 2013. ICSR welcomes conceptual or practical submissions to the robot design competition, based around the theme of companionship. Can a robot offer companionship? Could a robot friend be your confidante, your wing-man, your ally or your last defence against loneliness?

This year the ICSR robot design competition welcomes applicants from any background and in whatever format best suits your idea and your practice. Submissions may include posters, videos, prototypes, models, puppets, performances, sculpture etc. The only constraint is that your idea is centred on the theme of companionship and can be presented to
the conference audience in a busy room during an hour long session. We are looking for ideas for creating future robots that people will want to spend time with in a social sense, and the benefits that such robots may give to society or individuals.

The robot design competition is jointly run by Bristol Robotics Laboratory and Watershed’s Pervasive Media Studio. One person from each of the top 10 selected designs will be invited to attend half of a day of the conference (registration fees waived) to present their ideas. Following the presentation, conference attendees will vote for the top three entries, all of whom will receive certificates and prizes from our sponsors IET Robotics & MechatronIcs TPN <>.

* First Prize:     £400
* Second Prize: £200
* Third Prize:     £100

Each submission will need to be accompanied by a (maximum) 2 page summary including a concise abstract/synopsis of a maximum of 50 words. For further details, submission instructions and a downloadable flyer to post to your colleagues and students please visit: http://www.icsr2013.org.uk/competition.php

Deadlines for applications: Friday 13th September 2013, 17:00 GMT.

The RoboSavvy Humanoid Design Competition ends on September 22nd and is open to all. Robosavvy is looking for your help in gathering fresh ideas for the design of a new humanoid robot designated for entertainment and education. Their objective is to launch a new open-source humanoid robot that will look great and will be agile and smart at a reasonable cost. Think Bioloid, think Darwin, then think ‘a thing of beauty’.

The African Robotics Network (AFRON) is holding their 2nd Design Challenge in search of the “Ultra-affordable Robot”. The deadline has just been extended to January 2014, to allow greater opportunity for university students to participate as part of their semester projects. With support from the IEEE Robotics and Automation Society, this design challenge focuses on enhancements to the robot designs from the 2012 challenge, software development, and teaching plans. Details are below, and on the web at http://www.robotics-africa.org/2013-design-challenge. 

The 2012 Design Challenge emphasized an ultra-low-cost robot hardware platform in three categories: tethered, roaming, and all-in-one. The winning designs were all highly creative, and the Grand Prize in the tethered category went to Lollybot, a brilliant design by Tom Tilley of Thailand, costing just under 10 USD and incorporating two functional Lollipops. Starting with a generic dual-shock game controller, Lollybot can be built using commonly available tools anywhere in the world.

In the 2013 Design Challenge, our goal is to create incentives for designers to select any of the winning designs from 2012 and work on enhancements in one or more of 3 categories: 1) hardware 2) software, or 3) curriculum. This year, we are placing a special emphasis on Lollybot, encouraging next steps in the 3 categories: 1) enhance the Lollybot hardware design, simplifying assembly, increasing robustness, adding useful features, 2) extend and improve the open-source software for Lollybot, and 3) create exciting lesson plans using the Lollybot. In addition, there is a special ”community challenge” for participants who organize a robotics workshop for students using one of the winning designs, with or without enhancements.

We look forward to your participation!

Best regards,
Ayorkor Korsah & Ken Goldberg
co-Founders, African Robotics Network

Dash is the first product to launch today on Dragon Innovation‘s new hardware crowdfunding site. Dragon Innovation was founded in 2009 by Scott Miller and Herman Pang, ex iRobot and Hasbro. Dragon are partnering with GE, Qualcomm and freescale to bring us this new hardware crowdfunding site, which seems to be nicely positioned to accelerate startups somewhere in between Quirky, IndieGogo and the nuts and bolts of real world accelerators. Of course, Dragon are also behind Bolt, Boston’s new hardware accelerator.

The first 5 products on the crowdfund site include: Dash, the cockroach inspired robot; Mimo, a smart baby body monitor; Ollie, a slim flat multipurpose tool; LIMBERboard, a flexible wearable microcontroller board; and RunNRead, making reading while exercizing easy. It’s not clear whether the Dragon site plans to be more than just a shopfront for Dragon products but Dash is a cool little robot.

The Dash team from Berkeley Biomimetics Millisystems Lab have turned their research into an affordable, educational arduino based cockroach inspired robot kit. The manufacturing process is even more interesting. Dash is made using smart composite microstructures, or SCM, a technique allowing flexible joints or moving components to be made from the same sheet of material as more rigid body or limbs.

The SCM material is a sandwich of cardboard, plastic, and adhesive. We laser cut windows in the cardboard, leaving only the flexible polymer behind. This allows the windows to flex like a hinge. By cutting these hinges in certain locations and patterns, we can build up complex folded mechanisms such as hips, joints, and transmissions. As a result, Dash is very quick to fabricate, and design changes are easy. [Dash Robotics]

Of course, any product from the Berkeley Biomimetics Millisystems Lab is leveraging years of research into things like gecko adhesion, cockroach running and dragon fly flight. The springiness of natural animal locomotion has been incorporated into the mechanics of Dash’s design, enabling Dash to move and turn quickly without needing heavy, expensive servos or powerful processors.

What does it look like to an entrepreneur bootstrapping themselves through the early stages? I talk to Saurabh Palan, Founder and CEO of Mighty Carma, about the process. Firstly, Saurabh has just come through a few months of intense iteration (worth a whole nother blog post or two) in which he’s talked to potential customers, changed his design, talked to potential investors, changed his design, talked to more potential customers etc.

Crowdfunding was not Saurabh’s first choice. Saurabh’s first choice was to find a channel partner, who would then invest in him directly, or make investing in him appealing to investors due to the large market potential. Makes sense on paper but takes a lot of time that rarely pays off. Paul Graham from Y Combinator has written a great post “Do things that don’t scale” touching on that issue.

Along the way, Saurabh’s company changed its focus from robotics product to consumer automotive product. In technical terms, Mighty Carma is working on a Smartphone-based Advanced Driver Assistance System (ADAS). Steve Blank has also just written a great post on how robotics companies find their MVP and prove their business model by moving away from the robots.

It wasn’t Saurabh’s second choice to go to a crowdfunding campaign either. His preferred route is still to get direct investment or perhaps to get into a hardware accelerator like Lemnos Labs, Bolt, Haxlr8r, AlphaLabs or Highway1, the new PCH International accelerator.

50% of crowdfunding campaigns fail. While there are a lot of great hardware success stories like Ouya and Pebble, it is risky for the startup/entrepreneur. There are a lot of #fails. As an entrepreneur, you have to ask: how many times are you willing to take the risk? How will this impact on investor confidence? See my blog posts; “Crowdfunding Robots“, “New Funding Sources for Robotics“, “3 Reasons to Crowdfund a Robot” and “A Botiful Story“.

I asked Saurabh why he’s considering crowdfunding. “The cost and MVP fundamentals for the hardware are very different from the software company. It is easier to build an app, ship it and then fix what’s broken. You can easily do user testing as well as get feedback from customers who may want different things from what you have. For hardware, on the other hand, it’s very difficult to do consumer testing as we may just have a couple of 3D printed, hand-made prototypes.”

“Even though it’s open-source and cheap, building hardware comes at a cost. Crowd-funding allows us to show that prototype to a larger audience, get feedback, and test if this is something people will buy, if we manufactured it. Also with crowdfunding, it is easier to test ideas, and if it fails, you have lost a few months of work and some small cash, and if it worked, you can be the next big thing.”

How will you choose a crowdfunding platform?

“Both Kickstarter and Indiegogo are great platforms. However, after the changes made to rules on Kickstarter, it is difficult to get projects approved on Kickstarter, especially if it’s a hardware project. Kickstarter fails to understand how hardware works. They expect you to show a real product, not a 3D rendering of what it would be like. It is OK to show 3D printed product as long as they also allow the renderings for what users will get. This matters a lot as without 3D, the projects lack color, design details and also in some cases functionality.”

“Indiegogo on the other hand, lives and breathes hardware. They are based in San Francisco, right in the middle of the most innovative place on earth. They understand that it is very expensive to make hardware, also the chances of success is high when consumers are able to see the final product, even if it is in rendering.”

“Though Kickstarter has an advantage of wider audience and million dollar success, it is difficult to repeat the same on Kickstarter, due to their new rules. Indiegogo on the other hand is very open. You can not only show 3D, but also sell multiple units of the same product. (Approx 10,000 users bought more than 1 Pebbles.)”

Currently Saurabh is finalizing product design and looking for creatives to help him with marketing materials, pictures and videos for a crowdfund campaign. Many successful campaigns these days also employ marketing companies or professionals to grow customer base and create media interest. Saurabh will be searching Angel.co, LinkedIn and Craigslist for people with the skills he needs and hopes that tapping his existing networks will be sufficient for his crowdfund campaign. He expects to be going to meetups all that month, talking up his campaign, as well as approaching groups in the same space. He’s found that interest groups have been useful in giving him good feedback.

What are the benefits, outside of pre-orders, in crowdfunding?

“For innovative product, crowd-funding helps build a brand name. For example if Pebbles was not crowd-funded, Apple or Sony would have made their product irrelevant. However, due to the brand name, Pebbles is identified as the 1st on many that followed. Also it helps a great deal in raising money. (At least that’s what I have heard. One example is Romotive which did not get a single investor on demoday at Techstars, but were able to raise $5MM after $100k kickstarted campaign.)”

What are the risks to you?

“The risk are enormous. If crowdfunding is successful: 1. Meeting deadline to deliver product 2. Sorting supply chain. 3. Certifications (FCC, CE etc) 4. Setting up scalable manufacturing.”

“If it is not successful: 1. Now the idea has become public, so competitors know what we have and how they can better it.  2. Raising money becomes even more difficult.”

What the rewards are?

“Most rewarding thing is that you get to know from the customers directly if they want this or not. Also its a great marketing tool.”

We’ll follow up Saurabh’s progress with a Mighty Carma crowdfunding campaign as it happens. It’s easy to be wise in hindsight but it’s very hard to navigate the risks and rewards in real time.

While I love getting robots in the mail, crowdfunding sites are also good for supporting a whole range of robot related activities. The 3rd annual Robot Film Festival just launched a Kickstarter campaign to complement ticket sales on Eventbrite. This year, the Robot Film Festival is at Bot&Dolly studios in San Francisco on July 20-21, after very successful previous events in New York.

The Robot Film Festival was founded by Heather Knight and Marek Michalowski as a way of showcasing a diverse range of robotic visions, both real and fictional, in a thought provoking and entertaining fashion. The festival also serves to create a cultural snapshot of the current state of robotics.

Most crowdfunding sites are vehicles for cultural or charitable projects rather than shopfronts for physical goods, so this is a robot project likely to reach it’s very reasonable target. And while ticket sales are only going to be of interest to those in the Bay Area in July, the Kickstarter campaign has rewards for interested people anywhere.

Robot Adam Z1 from David Hanson

Some of the other robots on crowdfunding sites at the moment include both projects and products, hardware and software, complete robots and controller boards/shields. Projects include;

• Neko (an oil painting robot)  $1008 / $3000 funded with 18 days to go
• Superbolt Theater (taking their play The Uncanny Valley, about love between man and robot, to the Edinburgh Film Festival) $4307 / $7000 funded with 4 days to go
• RiPPLe (a high schooler prototyping a low cost humanoid robot) $1515 / $5500 funded with 11 days to go
• Hex (a humanoid platform out of Baltimore Hackerspace)$772 / $35,000 funded with 33 days to go
• Robot Adam Z1 (David Hanson’s project to get more smarts into a cute robot ) $3408 / $300,000 funded with 35 days to go
• Coralbots (nonprofit science team using swarm robotics to save coral reefs) $10,830 / $30,000 with 30 days left

Nessie 4 from Coralbots

Products include;

• mOwayduino (an affordable small wheeled platform with range of programming languages) $8452 / $50,000 funded with 33 days to go
• Rapiro (humonoid robot kit for Raspberry Pi) $35,170 / $20,000 with 55 days to go
• Bugzy (a wireless remote controlled robot bug) $0 / $5000 funded with 57 days to go
• Bot-Logic (a full hexapod kit or just the arduino logic shield) $3509 / $10,000 funded with 13 days to go
• Foldimate (industrial laundry folding machine) $7018 / $250,000 funded with 10 days to go
• Sunnybot (smart moving solar reflector) $6138 / $200,000 funded with 18 days to go
• RK-1 (wifi mobile arduino robot) $2674 / $5000 funded with 10 days to go
• Fiona (smart AI interface from Adele Robots) $17,462 / $100,000 funded with 30 days to go

mOwayduino from Spanish company MiniRobots

Components include;

•  TiltyIMU (open source robotics controller for self balancing robots) $170 / $5000 funded with 29 days to go
• Motor PiTX (motor controller for Raspberry Pi robots) $2535 / $1500 funded with 11 days to go

Successful recently finished campaigns include;

• Linkbots from Barobo $45,792 / $40,000
• Sparki from Arcbotics $188,786 / $60,000

Sparki from Arcbotics

Seagull chasing a drone at Engadget Expand SF

Speakers at Engadget’s weekend expo include: Steve Cousins of Willow Garage, Chris Anderson of 3D Robotics, Marc Raibert of Boston Dynamics, Russ Angold of Ekso Bionics, and Catherine Mohr of Intuitive Surgical. The panels are all online at Engadget and linked to below.

I’ve included a list of some (not all) of the videos in rough order of the event:

Demo of Ekso Bionics

Science Fiction Panel: with Daniel H. Wilson, John Salzi and Veronic Belmont

Future of Technology?

Robopocalypse: with Chris Anderson of 3d robotics

Robopocalypse: with Marc Raibert of Boston Dynamics

Robopocalypse: with Steve Cousins of Willow Garage

Robopocalypse: panel

Marc Raibert backstage

Better Living Through Technology Panel: with Russ Angold of Ekso Bionics and Catherine Mohr of Intuitive Surgical

Insert Coin Winners backstage: with Ziphius aquatic drone

Insert Coin demo: Ziphius aquatic drone

Insert Coin demo: cSpring humanoid robot

In my opinion, the International Consumer Electronics Show used robots gratuitously, out of context and without benefit to robotics companies. It’s a category problem more than anything else and is repeated across consumer electronics, media and popular culture.

CNET used robots in the showreel for the “post mobile future of technology” panel, yet didn’t discuss automation or artificial intelligence. CES used robots in their general showreel, playing in all the shuttle buses and PR for CES2013, and yet buried the “robot tech zone” at the back of beyond. It would have been good to see the poster robot, Amp, in production or in person. But also, there were far more robots out of the robot zone than inside it. Robotics has jumped the shark. Consumer robotics is alive and well, but it doesn’t resemble the PR.

We may have reached a tipping point where having a robot zone does everyone a disservice. Outside of a couple of very well known and popular robots, like Paro and Pleo, the robot zone was primarily filled with component company booths. Most robot companies, like iRobot, were scattered across the entire show, staying closer to their vertical areas. Or they were in the new innovation and startup areas. And you couldn’t rely on the CES categories if you wanted to find a robotics company somewhere else.

The CES 2013 official guide lists only 59 robot companies (and they are scattered across the whole convention area). It’s immediately obvious that major companies are missing from the list. iRobot, Parrot and Moneual all had “ROBOT” proudly posted all over their displays and were doing thriving business in the home appliance areas. However, they weren’t listed as robot companies.

Parrot and Moneual are going head to head in the internet of things with their new smart pot plant sensors. And although they are reaching into other areas of automation and robotics, Moneaul in particular was milking the packaging device of calling everything a “robot”, with their robot vacuum, mop and air purifier.

There were also some great robotics companies in the Eureka Tech Zone with Modular Robotics, RoadNarrows, Interbots and Robotex, to name just a few. Modular Robotics new Cubelets kit is both cheaper and better. They’ve added a lego conversion, so that you can attach lego to your Cubelets and go wild building. They’ve also added a bluetooth cube and made them hackable.

Interbots had their new soft touchable and expressive robot toy aimed at children with autism spectrum disorder. RoadNarrows was displaying a nice lightweight 3D printed 5 DOF robot arm and 3D vision system, which highlights the changes that digital manufacturing processes are making in robotics.

And Robotex were selling a light weight consumer version of their security robotic platform. “Avatar” is ios and android compatible, via bluetooth and is open source. Avatar also comes from a company that knows how to build reliable and robust robots and is selling for only $299.

You can also find plenty of robotics hidden in the automotive sections. (Most of the buzz I heard at CES was about driverless vehicles and assistive technologies.) But it’s clear that car companies don’t always see much benefit in identifying as a ‘robotic’ technology.

There’s the problem. What is the benefit to a robotics company in being categorized as ‘robot’ when your market may be home automation or health care?

And it was sad not to see Amp in ‘person’. It sure looked like Amp was the poster robot for CES and yet production has been on hold since the recession hit.

Bob Christopher was CEO of Ugobe, the company that made Pleo, the robot dinosaur, one of the first successful consumer robotics products. Greg Appelhof is the CEO of TRG, a global retail company specializing in emerging technologies.

Together they have written “The 2 Year Itch”, a paper advising hardware and robotics consumer technology companies on the finer points of surviving in the retail market.

In this video interview with Bob Christopher, the second in our robot startup series, he shares stories from the starting of Ugobe with Caleb Chung, and their first meetings with Greg Appelhof while they were doing stealth guerilla marketing at CES, the Consumer Electronics Show.

Bob talks about developing an understanding of your retail partners balanced against a clear understanding of your product and your company’s ‘dna’ or core principles. He explains the term, 2 year itch as more than just a critical period in company lifespan when poor inventory management can sink a successful product. It also represents the uneasy position of a consumer hardware company bookended between the costs of manufacturing and the revenue of retail.

You can download a copy of  The 2 Year Itch here.

Read more from our Startup Series.