A group from Floreano Lab, EPFL and NCCR Robotics has today published their novel variable stiffness fibre with self-healing capability.

Soft “hardware” components are becoming more and more popular solutions within the field of robotics. In fact softness, compliance and foldability bring significant advantages to devices by allowing conformability and safe interactions with users, objects and unstructured environments. However for some applications, the softness of components adversely reduces the range of forces those devices can apply or sustain. An optimal solution would be having components able to vary their softness according to the needed task.

The fibre has a metal core, consisting of low melting point alloys (LMPA), which is contained within a pre-stretched silicone tube. At room temperatures the LMPA is a solid, thus, the fibre is stiff and behaves like a thin metal wire. But when an electrical current is passed through a copper wire coiled around the tube, the LMPA inner core is warmed above 62 ^oC and melts, thus, the fibre becomes up to 700 times softer and 400 times more deformable.

The second advantage is that if the metallic core breaks it just needs to be heated and — voila! The fibre is fixed! And to top it off, the changing of states occurs in tens of seconds (depending on the current injected and the dimension of the LMPA core).

The fibre has a myriad of real-world applications in the fields of mobile robots, wearable devices and soft systems. Currently, the team is using the fibre to create multi-purpose foldable drones. In fact, the fibre can be morphed into different shapes that are preserved after cooling, ie the four arms of the drone can take different functional morphologies, i.e. deployed in a quadrotor-like configuration for aerial locomotion or bent towards the ground in a four-wheeled configuration for terrestrial locomotion.

Future applications that the team is investigating include in endoscopes and other medical applications, where instruments need to be soft and pliable as they are exploring delicate body cavities, but then need to be able to penetrate resistive biological tissues (e.g. for a biopsy) once they have reached their desired location.

Reference

Tonazzini, A., Mintchev, S., Schubert, B., Mazzolai, B., Shintake, J. and Floreano, D. (2016), Variable Stiffness Fiber with Self-Healing Capability. Adv. Mater.. doi:10.1002/adma.201602580

The octobot is powered by a chemical reaction and controlled with a soft logic board. A reaction inside the bot transforms a small amount of liquid fuel (hydrogen peroxide) into a large amount of gas, which flows into the octobot’s arms and inflates them like a balloon. A microfluidic logic circuit, a soft analog of a simple electronic oscillator, controls when hydrogen peroxide decomposes to gas in the octobot. Image credit: Lori Sanders/HarvardSEAS

By: Leah Burrows

A team of Harvard University researchers with expertise in 3D printing, mechanical engineering, and microfluidics has demonstrated the first autonomous, untethered, entirely soft robot. This small, 3D-printed robot — nicknamed the octobot — could pave the way for a new generation of completely soft, autonomous machines.

Soft robotics could revolutionize how humans interact with machines. But researchers have struggled to build entirely compliant robots. Electric power and control systems — such as batteries and circuit boards — are rigid and until now soft-bodied robots have been either tethered to an off-board system or rigged with hard components.

Robert Wood, the Charles River Professor of Engineering and Applied Sciences and Jennifer A. Lewis, the Hansjorg Wyss Professor of Biologically Inspired Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) led the research. Lewis and Wood are also core faculty members of the Wyss Institute for Biologically Inspired Engineering at Harvard University.

“One long-standing vision for the field of soft robotics has been to create robots that are entirely soft, but the struggle has always been in replacing rigid components like batteries and electronic controls with analogous soft systems and then putting it all together,” said Wood. “This research demonstrates that we can easily manufacture the key components of a simple, entirely soft robot, which lays the foundation for more complex designs.”

The research is described in the journal Nature.

“Through our hybrid assembly approach, we were able to 3D print each of the functional components required within the soft robot body, including the fuel storage, power and actuation, in a rapid manner,” said Lewis. “The octobot is a simple embodiment designed to demonstrate our integrated design and additive fabrication strategy for embedding autonomous functionality.”

Octopuses have long been a source of inspiration in soft robotics. These curious creatures can perform incredible feats of strength and dexterity with no internal skeleton.

Harvard’s octobot is pneumatic-based — powered by gas under pressure.  A reaction inside the bot transforms a small amount of liquid fuel (hydrogen peroxide) into a large amount of gas, which flows into the octobot’s arms and inflates them like a balloon.

“Fuel sources for soft robots have always relied on some type of rigid components,” said Michael Wehner, a postdoctoral fellow in the Wood lab and co-first author of the paper. “The wonderful thing about hydrogen peroxide is that a simple reaction between the chemical and a catalyst — in this case platinum — allows us to replace rigid power sources.”

To control the reaction, the team used a microfluidic logic circuit based on pioneering work by co-author and chemist George Whitesides, the Woodford L. and Ann A. Flowers University Professor and core faculty member of the Wyss. The circuit, a soft analog of a simple electronic oscillator, controls when hydrogen peroxide decomposes to gas in the octobot.

The octobot, here with fluorescently dyed fugitive inks (red) and hyperelastic actuator layers (blue), is fabricated by moulding and 3D printing. Image courtesy: Lori Sanders/Harvard SEAS

“The entire system is simple to fabricate, by combining three fabrication methods — soft lithography, molding and 3D printing — we can quickly manufacture these devices,” said Ryan Truby, a graduate student in the Lewis lab and co-first author of the paper.

The simplicity of the assembly process paves the way for more complex designs. Next, the Harvard team hopes to design an octobot that can crawl, swim and interact with its environment.

“This research is a proof of concept,” Truby said. “We hope that our approach for creating autonomous soft robots inspires roboticists, material scientists and researchers focused on advanced manufacturing,”

The paper was co-authored by Daniel Fitzgerald of the Wyss Institute and Bobak  Mosadegh, of Cornell University.  The research was supported by the National Science Foundation through the Materials Research Science and Engineering Center at Harvard and by the Wyss Institute.

Visit the new Harvard Robotics website to learn more about robotics at Harvard.

Research reference:

http://www.nature.com/nature/journal/v536/n7617/full/nature19100.html

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

Caterpillar micro-robot sitting on a finger tip.
Credit: Source: FUW

Researchers at the Faculty of Physics at the University of Warsaw, using the liquid crystal elastomer technology, originally developed in the LENS Institute in Florence, demonstrated a bioinspired micro-robot capable of mimicking caterpillar gaits in natural scale. The 15-millimeter long soft robot harvests energy from green light and is controlled by spatially modulated laser beam. Apart from travelling on flat surfaces, it can also climb slopes, squeeze through narrow slits and transport loads.

A small 3-D printed ionic polymer-metal composite soft robotic hand. National Science Foundation researchers are working to transform this material into artificial muscles. Credit: Kam K. Leang. University of Utah

Forget steel and aluminum. The robots of tomorrow may be able to squish, stretch and squeeze.

Novel robotic devices, part of the emerging field of soft robotics, offer many advances over conventional robots. Soft robots can more easily maneuver in tough spaces. They can better interact with humans, making them excellent assistants for elderly people. And one day they may lead to high-tech artificial muscles: a life-changing innovation for millions of disabled people around the globe.

James Carrico, a Ph.D. graduate student at the University of Utah, displaying a small 3-D printed ionic polymer-metal composite soft robotic hand. Credit: Kam K. Leang

Creating artificial muscles requires not only developing a powerful, flexible material, but figuring out how to precisely control and cleverly manufacture it. That’s the mission of Kwang Kim of the University of Nevada, Las Vegas and his National Science Foundation (NSF)-funded team.

Kim is lead investigator on a NSF award pairing a diverse group of researchers — at four U.S. universities plus research institutions in Japan and South Korea — to transform a novel polymer-based material into artificial muscles. The research is supported through NSF’s Partnerships for International Research and Education (PIRE) program, which supports innovative, global research collaborations across all fields of science and engineering.

PIRE leverages U.S. funding and expertise to tackle global challenges. Kim’s U.S. team is working with researchers from the Korea Advanced Institute of Science and Technology (KAIST) and Japan’s National Institute of Advanced Industrial Science and Technology, both known for strong expertise in robotics. (KAIST, for example, won the recent Robotics Challenge, hosted by the Defense Advanced Research Projects Agency.)

One of the big challenges in soft robotics is finding the right material. “It has to be soft, but it also has to produce enough power to do lots of different things,” Kim said. His team is using a type of synthetic material called Ionic Polymer-Metal Composites, which is a kind of electroactive polymer — meaning running electricity through the material makes it change shape.

The PIRE award will work to transform electroactive polymers, a type of material that changes shape when electricity runs through it, into artificial muscles. Credit: Kwang J. Kim, University of Nevada, Las Vegas; Kam K. Leang, University of Utah (both formerly of University of Nevada, Reno)

“In robotics you’ve got to be able to move and you’ve got to be able to sense,” said Kam Leang, an associate professor at the University of Utah Robotics Center and a co-investigator on this project. Traditional robots use electric motors to do the former. “In this PIRE, we are using the electroactive polymer itself.”

Electroactive polymers can also be used to sense motion, making them a great candidate for soft robotics. Leang and his colleagues have also devised a way to 3-D print the material. His component of the PIRE research is focused on how to scale up the manufacturing, as well as devising ways to better control the motion of the polymer. Others are working to better understand — and improve — the polymer material to make it more responsive, strong and affordable.

The project, which received NSF funding last fall, is still in its early stages. Kim, who has been working in electroactive polymers for nearly two decades, said soft robotics itself is still a relatively new field.

“I’m learning every day.”

Investigators: Paul Oh, Kam Leang, Kwang Kim, Chulsung Bae, Maurizio Porfiri

Related Institutions/Organizations: New York University, The University of Utah, University of Nevada Las Vegas, Rensselaer Polytechnic Institute

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

• National Robotics Initiative celebrates five-year anniversary
• NSF and partners award $37M to advance nation’s co-robots
• Speedy robots may someday run to the rescue

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

Today, a team from LSBI, EPFL and NCCR Robotics present their latest stretchable biphasic (solid-liquid) thin metal film in the journal Advanced Materials. To build the films, first a substrate (a base that the film will be built upon) of polydimethylsiloxane (PDMS) is lain. On top of this, a metallic bilayer is formed by evaporating gallium onto a 60nm thick sputtered gold film. The resulting metallic film has two distinct phases: a solid AuGa₂ alloy immersed in liquid gallium that has a melting point of 29.8 ^oC. The thinness and deposition method of the biphasic film allow for fine and complex shape patterning using lithography techniques, similar to those obtained in metal films on rigid substrates.

The idea of using biphasic (i.e. solid and liquid) elements within the film is that when it is bent or stretched, small cracks form within the solid alloy layer, but the liquid layer is on hand to seep into the gaps and ensure continued electrical conductivity. This elegant solution really seems to work – when tested in the lab under repeated strain and tension, the films retained low sheet resistance (< 0.5 Ω/sq), low gauge factor (sensitivity to strain) (≈ 1) and the ability to stretch by 400 % a million times without affecting function.

Reference

A. Hirsch, H.O.Michaud, A.P. Gerratt, S. de Mulatier and S.P. Lacour, “Intrinsically stretchable biphasic (solid-liquid) thin metal films,” Advanced Materials, 2016. Doi: 10.1002/adma.201506234

Team’s silicone rubber gripper can pick up egg, CD & paper, and identify objects by touch alone

By Adam Conner-Simons, MIT CSAIL

Robots have many strong suits, but delicacy traditionally hasn’t been one of them. Rigid limbs and digits make it difficult for them to grasp, hold, and manipulate a range of everyday objects without dropping or crushing them.

Recently, CSAIL researchers have discovered that the solution may be to turn to a substance more commonly associated with new buildings and Silly Putty: silicone.

At a conference this month, researchers from CSAIL Director Daniela Rus’ Distributed Robotics Lab demonstrated a 3-D-printed robotic hand made out of silicone rubber that can lift and handle objects as delicate as an egg and as thin as a compact disc.

Just as impressively, its three fingers have special sensors that can estimate the size and shape of an object accurately enough to identify it from a set of multiple items.

“Robots are often limited in what they can do because of how hard it is to interact with objects of different sizes and materials,” Rus says. “Grasping is an important step in being able to do useful tasks; with this work we set out to develop both the soft hands and the supporting control and planning systems that make dynamic grasping possible.”

The paper, which was co-written by Rus and graduate student Bianca Homberg, PhD candidate Robert Katzschmann, and postdoc Mehmet Dogar, will be presented at this month’s International Conference on Intelligent Robots and Systems.

The hard science of soft robots

The gripper, which can also pick up such items as a tennis ball, a Rubik’s cube and a Beanie Baby, is part of a larger body of work out of Rus’ lab at CSAIL aimed at showing the value of so-called “soft robots” made of unconventional materials such as silicone, paper, and fiber.

Researchers say that soft robots have a number of advantages over “hard” robots, including the ability to handle irregularly-shaped objects, squeeze into tight spaces, and readily recover from collisions.

“A robot with rigid hands will have much more trouble with tasks like picking up an object,” Homberg says. “This is because it has to have a good model of the object and spend a lot of time thinking about precisely how it will perform the grasp.”

Soft robots represent an intriguing new alternative. However, one downside to their extra flexibility (or “compliance”) is that they often have difficulty accurately measuring where an object is, or even if they have successfully picked it up at all.

That’s where the CSAIL team’s “bend sensors” come in. When the gripper hones in an object, the fingers send back location data based on their curvature. Using this data, the robot can pick up an unknown object and compare it to the existing clusters of data points that represent past objects. With just three data points from a single grasp, the robot’s algorithms can distinguish between objects as similar in size as a cup and a lemonade bottle.

“As a human, if you’re blindfolded and you pick something up, you can feel it and still understand what it is,” says Katzschmann. “We want to develop a similar skill in robots — essentially, giving them ‘sight’ without them actually being able to see.”

The team is hopeful that, with further sensor advances, the system could eventually identify dozens of distinct objects, and be programmed to interact with them differently depending on their size, shape, and function.

How it works

Researchers control the gripper via a series of pistons that push pressurized air through the silicone fingers. The pistons cause little bubbles to expand in the fingers, spurring them to stretch and bend.

The hand can grip using two types of grasps: “enveloping grasps,” where the object is entirely contained within the gripper, and “pinch grasps,” where the object is held by the tips of the fingers.

Outfitted for the popular Baxter manufacturing robot, the gripper significantly outperformed Baxter’s default gripper, which was unable to pick up a CD or piece of paper and was prone to completely crushing items like a soda can.

Like Rus’ previous robotic arm, the fingers are made of silicone rubber, which was chosen because of its qualities of being both relatively stiff, but also flexible enough to expand with the pressure from the pistons. Meanwhile, the gripper’s interface and exterior finger-molds are 3-D-printed, which means the system will work on virtually any robotic platform.

In the future, Rus says the team plans to put more time into improving and adding more sensors that will allow the gripper to identify a wider variety of objects.

“If we want robots in human-centered environments, they need to be more adaptive and able to interact with objects whose shape and placement are not precisely known,” Rus says. “Our dream is to develop a robot that, like a human, can approach an unknown object, big or small, determine its approximate shape and size, and figure out how to interface with it in one seamless motion.”

This work was done in the Distributed Robotics Laboratory at MIT with support from The Boeing Company and the National Science Foundation.

RELATED

Paper: “Haptic Identification of Objects using a Modular Soft Robotic Gripper”

Bianca Homberg

Daniela Rus

Distributed Robotics Lab

[article on csail.mit.edu]

The Jaeger-Lipson coffee balloon gripper. Its soft end effector adapts itself to the object it grasps. Source: John Amend

Soft robots are versatile, often much safer, more energy-efficient, robust and resilient than their more rigid counterparts. But one of the biggest challenges facing soft robotics is control – often, classical approaches don’t apply. The answer may lie in morphological computation, an idea that stems from biological systems using their bodies to control basic actions.

Industrial Networking and Engagement Day on Soft Technologies

Explore the possibilities of soft technologies and soft robotics in your field!

October 8, 2015
Bristol, UK

Novel designs in soft robotics reference simplicity as well as versatility. The Jaeger-Lipson coffee-balloon gripper is one example. Essentially a balloon, it’s filled with ground coffee and can be either soft or hard depending on the air pressure within it. It can grasp objects using a simple one-dimensional control variable (switching the vacuum on or off). By exploiting its soft morphology, the end effector adapts itself to the object without the need for any explicit modelling or control.

Morphological computation proposes that at least some aspects of control (such as walking or grasping) can be outsourced to the body as these functions are already “encoded” within it. Another way to see it is that the body can be exploited as a computational resource. This makes a task much easier, since part of the “work” will already have been done by the body, reducing the complexity of the robot’s computational problems and the corresponding control and learning tasks.

The soft body of the octopus has potential as a computational resource.

So what kind of computation can we carry out in the physical bodies of robots? Biological systems have to take sensory information and interpret or transform it into sensible actuation signals. The computational process is a dynamic mapping of continuous input streams onto output streams, with a feedback loop through the environment. This could be, for example, a nonlinear controller that is implemented in the morphology to stabilize running – a controller is nothing other than a dynamical system, after all. In the case of morphological computation, this system is simply part of the body instead of an algorithm in some external, digital computational unit.

Fundamentally different from digital computing processes, morphological computation is not based on a Turing machine with discrete steps and finite time; it takes place in the continuous, analogue realm and is carried out directly in the body.

It can also be broadened out beyond the shape and form of body parts, into parameters that describe its dynamics, such as stiffness, friction, or damping. The dynamic parameters of the environment also shape the type of computation. For example, a compliant leg interacts with the ground (when it impacts), and a soft hand deforms by grasping an object.

Some background

Asimo has rigid body parts. While it is an ingenious piece of hardware, its body is not useful for morphological computation.

Recent studies in morphological computation [1][2] suggest that a computationally powerful body needs to exhibit highly complex dynamics (i.e. high-dimensional state space, nonlinearities and under-actuation). But in most classical robot designs, such as the Asmio robot and many industrial robots, these properties are deliberately suppressed as complex dynamics can interfere with modelling and control.

The concept of morphological computation has been widely used in robotics for some time now. Some nice examples are listed by Pfeifer and Bongard in their influential book “How the body shapes the way we think” [3].

Many of these robots were built using a combination of bio-inspiration, intuition, and clever engineering. Until recently, there were no clear guidelines for their design.

To fill this gap, we developed two theoretical, mathematical models [1],[2] that attempt to describe how bodies can be exploited as computational resources. In order to provide a descriptive generic model, we used networks of simple mass-spring damper systems – a good approximation for biological, but also soft, robotic bodies.

Caption: (a) The Cornell passive dynamic walker (Collins et al., 2001); (b) Wanda by Ziegler et al., 2006; (c) Puppy and (d) Stumpy by Fumiya Iida (Source: Iida and Pfeifer, 2004)

The underlying idea is to use morphology as a computational resource to emulate complex behaviours. The range of possible computation is impressive. Theoretically, there are almost no limits.

We were able to show that physical bodies can be used to emulate complex nonlinear differential equations (e.g. nonlinear controllers). We demonstrated setups to emulate nonlinear limit cycles that are highly robust and are even able to generalize beyond their learned data sets. Such limit cycles can be used to produce a control signal for locomotion. We were even able to demonstrate the use of the body as a switch between different limit cycles (behaviours) based on physical inputs (forces applied to the system) that could come from the environment. The implications are that the body can also serve as a type of sensor, enabling the robot to sense change through its soft body and react appropriately.

One possible application could be a robot that is able to “feel” the weight on its body, enabling it to adapt its locomotion by producing (computing) different limit cycles accordingly.

A robot that is able to “feel” the weight on its body and react appropriately by producing different limit cycles depending on the situation. Source: Hauser, H and Füchslin. RM and Nakajima, K. [4]

Building real robots

Theoretical results aside, a number of real-world platforms have exploited soft complex bodies as a computational resource. For example, in the EU project OCTOPUS we showed that a passive silicone arm (inspired by the octopus) can be used to carry out complex computational tasks [5 and 6].

Caption: (a) Passive soft silicone arm from [6]; (b) modular pneumatically driven robot arm, by TUM; (c) Kitty, a robot with compliant spine [7] (d) NASA’s superball robot [8]

We built a quadruped robot with compliant spine that we used as a computational resource to control its locomotion [7]. We also demonstrated, in a more industrial setting, that a modular, pneumatically-driven robot arm (developed at TU Munich by Martin Eder) can be exploited via morphological computation [paper close to submission]. Another example is NASA’s tensegrity robot “SuperBallBot,” with applications in exo-planetary exploration [8].

Implications and outlook

Morphological computation provides us with a new viewpoint: instead of perceiving their complex dynamics as a problem, we can instead embrace and exploit this hidden superpower of soft bodies. There are some interesting implications:

• Soft robots can exploit their bodies for computational tasks that can make them more robust, faster (they respond in real time) and, potentially, more energy efficient than their hard counterparts, as they work with rather than against their body dynamics.
• The addition of smart materials enables body parts to take over not only actuation, but also the task of sensing the environment and processing this information. This may even extend to situations where parts of the robot break down, resulting in highly resilient, adaptive and intelligent machines.
• A morphological computation approach will allow us to design robots that can easily switch from one behaviour to another. For example: from a stable limit cycle (during locomotion) to an exponentially stable equilibrium point (for a reaching task), e.g. [10].
• The concept can be applied to a range of intelligent structures. For example: smart furniture that adapts to the movement of its user, haptic interfaces and wearable soft devices for rehabilitation or teaching novel movements (e.g. a new sport). Even smart architecture that reacts to environmental changes.
• In the future, self-assembling systems could also exploit morphological computation. Since the morphology defines the function/computation, by changing the morphology, we can “reprogram” the machine.

Because of their complex dynamics, soft robots potentially have a more computationally powerful body than rigid robots. Morphological computation turns the complexity, which has been perceived as a disadvantage in robotics, into a powerful benefit. Looking at the work done so far, we believe there is great potential for other applications and novel ideas and we are looking forward to the future.

Want to learn more about soft robotics? Come to the  Industrial Networking and Engagement Day on Soft Technologies on October 8, 2015 in Bristol, UK. This is event is geared toward people from the private sector who want to explore the possibilities of soft technologies and soft robotics in their field.

If you liked this article, you may also be interested in Helmut Hauser’s presentation on Morphological Computation at the ShanghAI Lectures 2013. You may also enjoy:

• Soft robotics for adaptive building facades
• Two new soft robotics competitions announced by Soft Robotics Toolkit
• Robots Podcast: Soft Robotics Toolkit, with Donal Holland
• Robot Startup Series #7: Interview with Soft Robotics’ Carl Vause
•  Soft robotics in space

References

[1] Hauser, H.; Ijspeert, A.; Füchslin, R.; Pfeifer, R. & Maass, W. “Towards a theoretical foundation for morphological computation with compliant bodies” Biological Cybernetics, Springer Berlin / Heidelberg, 2011, 105, 355-370 http://www.springerlink.com/content/j236312507300638/

[2] Hauser, H.; Ijspeert, A.; Füchslin, R.; Pfeifer, R. & Maass, W. “The role of feedback in morphological computation with compliant bodies” Biological Cybernetics, Springer Berlin / Heidelberg, 2012, 106, 595-613 http://www.springerlink.com/content/d54t39qh28561271/

[3] Pfeifer, R. and Bongard J. “How the body shapes the way we think: a new view of intelligence” MIT press, 2006.

[4] Hauser, H and Füchslin. R.M. and Nakajima, K. “Morphological Computation – The Physical Body as Computational Resource” in e-book on “Opinions and Outlooks on Morphological Computation”, Chapter 20,
ISBN 978-3-033-04515-6, 2014, – http://tinyurl.com/pjvey43

[5] Nakajima K.; Li T.; Hauser H.; and Pfeifer R. “Exploiting short-term memory in soft body dynamics as a computational resource” Journal Royal Society Interface, 6 November, 2014, vol. 11, no. 100, 20140437 – DOI: 10.1098/ rsif.2014.0437 http://rsif.royalsocietypublishing.org/content/11/100/20140437.short

[6] Nakajima, Kohei, Helmut Hauser, Tao Li, and Rolf Pfeifer. “Information processing via physical soft body” Scientific Reports 5 (2015) Article number: 10487, doi:10.1038/srep10487 http://www.nature.com/srep/2015/150527/srep10487/full/srep10487.html

[7] Q. Zhao, K. Nakajima, H. Sumioka, H. Hauser, and R. Pfeifer “Spine Dynamics as a Computational Resource in Spine-Driven Quadruped Locomotion”  IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), 1445 – 1451, 2013

[8] Caluwaerts, Ken, et al. “Design and control of compliant tensegrity robots through simulation and hardware validation.” Journal of The Royal Society Interface 11.98 (2014): 20140520 http://rsif.royalsocietypublishing.org/content/11/98/20140520

[9] McEvoy, M. A., and N. Correll. “Materials that couple sensing, actuation, computation, and communication.” Science 347.6228 (2015): 1261689.

[10] “, F. Corucci, M. Calisti, H. Hauser, and C. Laschi “Novelty-based evolutionary design of underwater morphing robots” International Conference on Genetic and Evolutionary Computation (GECCO 2015) [accepted]

[11] Hermans, Michiel, et al. “Trainable hardware for dynamical computing using error backpropagation through physical media.” Nature Communications 6 (2015).

The adaptive solar façade is assembled on the south side of the House of Natural Resources. (Photo: Marco Carocari)

By Arno Schlüter
Today, building envelopes tend to be static and unable to adapt to changing conditions. Now, for the first time, an adaptable façade has been used for the newly inaugurated House of Natural Resources (HoNR) that produces electricity and regulates light and heat generation.

The envelope of a building is of great importance to its energy balance, and insulation and air-tightness have improved significantly in recent years. But there is also significant untapped potential when it comes to contributing to the transition of our energy system towards renewable energy sources: the building envelope of a building, particularly the façade, can be designed to recover heat and generate electricity.

From rigid to dynamic structures

As the boundary between interior and exterior spaces, the façade influences the air, light and heat balance of a building significantly – and thus has a direct impact on the comfort of users. Both spaces are stochastic by nature: they change constantly and conditions are at best only vaguely predictable. And yet the envelope of a building is usually static, focusing on only one or just a few different situations. Today’s building envelope is rarely adaptable to changes in weather or the use of a room. This considerable potential for energy conservation and generation, as well as improved comfort, remains unused.

At the Chair of Architecture and Building Systems, we are researching approaches to make the building envelope more dynamic, efficient and adaptive. One example is the adaptive solar façade, which consists of individual modules mounted on a cable network on the façade. By adjusting the amount of solar radiation through the window, they can control the light and heat of the internal space and at the same time produce electricity through highly efficient thin-film solar cell modules. The adaptive solar façade is also very lightweight, so in contrast to traditional photovoltaic panels it can be mounted almost anywhere, including on existing buildings.

Soft robotics for adaptability

The soft actuator can move the module. (Photo: Professorship of Architecture and Building Systems)

The modules are moveable thanks to a new device, the soft robotic actuator, which originates from a new and promising field of robotics, soft robotics. It is made of flexible materials that take multiple forms when the pressure in the special chambers change. Such actuators are normally used mainly for prosthetic and biomimetic robots; we are now exploring and developing them for future energy and climate systems in buildings.

Our soft actuator is manufactured with a specially developed hollow casting process and the chamber is then filled with air. Valves control the air flow by pumping or releasing air to deform the actuator and thus move the solar element selectively. With soft actuators, we can control each adaptive solar façade module individually and rotate it on two axes, either on its own or in groups. This enables the modules to track the sun’s movement and generate power, use or limit solar power, create privacy or open up the view. An intelligent and adaptive regulator allows the façade to adapt to changing weather conditions and the habits and wishes of the user.

Prototype at the House of Natural Resources

A view of the adaptive solar façade from inside the building. (Photo: Marco Carocari)

Without soft actuators, such functionality would be possible only through a complex combination of several mechanical parts. These would be less durable and more expensive – making it unlikely that they would achieve widespread use in façades. In contrast, our actuator costs only a few francs when produced industrially. The soft actuator has been proven to be robust in cyclic tests in the laboratory; now it has to prove that it is just as effective in the harsh conditions of a building façade. To test this, along with various other factors, we have assembled a prototype façade of 50 modules on the south side of the House of Natural Resources (HoNR).

The module uses highly efficient copper indium gallium selenide (CIGS) thin-film solar cells for top performance: the solar cells are developed by the EMPA spin-off Flisom [1], our industrial partner in the project. First life-cycle calculations have shown that it would take only 18 months for the adaptive solar façade to offset the CO2 emitted in the module’s manufacture.

As part of the EU Climate-KIC’s Building Technology Accelerator flagship project [2], we are currently investigating how and in what form the adaptive solar façade, and thus the soft actuator, can be developed into a marketable product. If this is successful, our adaptive façade could contribute to the efficient generation of building energy and thus to energy transition.

Further information

House of Natural Resources HoNR

Website of the Chair of Architecture and Building Systems.

References:

[1] EMPA spin-off Flisom

[2] EU Climate-KIC BTA flagship project

Soft robotics combines the design of electromechanical systems with the study of soft and flexible materials, often inspired by biological systems. A growing number of research groups, companies, and individual designers and makers have been contributing to the field in recent years. The Soft Robotics Toolkit was launched in September 2014 and is intended to enable students, designers, and researchers to share and build upon each other’s work in this exciting area. The toolkit is a website containing documentation on the design, construction, and characterization of soft component technologies including sensors, actuators, and control boards.

In the seven months since its launch, the toolkit has had almost 250,000 page views by over 40,000 users in 150 countries. In light of the incredible outpouring of support from the community, the toolkit development team has announced two competitions for soft robotics design and research. The aim of these competitions is to recognize those who make soft robotics such an exciting area and to reward individuals and teams who advance the field.

The first competition, the 2015 Prize for Contributions in Soft Robotics, is intended to support and promote research that advances the field of soft robotics. The toolkit website currently contains documentation from seven research groups at Harvard and ETH, and further contributions from leading soft robotics groups at other institutions are forthcoming. Researchers are invited to submit original work to the toolkit in order to be considered for the prize. An international panel of expert judges will award one entry a grand prize of $5,000. Example entries might include new control architectures or component technologies, novel methods of modeling and analyzing compliant electromechanical systems, or new experimental procedures for characterizing soft devices.

The second competition, the Soft Robotics Design Competition 2015, rewards individuals and teams who create new and interesting devices using material they can find on the toolkit website. Example projects might include robots capable of manipulating delicate objects or of novel forms of locomotion, or improved control systems for soft robotic systems. Eligible designs may be entirely “soft,” or may combine traditional rigid robotic elements with soft components. The only limitation (besides entrants’ imaginations) is that the design must make use of at least one component technology from the Soft Robotics Toolkit website. The judging panel, composed of designers and researchers from industry and academia, will select a winning entry and two runners-up for prizes of $3,000 and $1,000 respectively.

In order to be considered for the awards, entrants must register by May 15^th, with the final project documentation due June 15^th. The response so far has been fantastic. To date, 66 teams have registered to participate, with 23 countries and 34 universities represented. For more information on how to participate, please see the competition website.

Baymax, Chris Atkeson and Hiro from Disney’s Big Hero 6. Source: Chris Atkeson

Baymax, the lovable, inflatable robot star of Disney’s recent hit, Big Hero 6, is far from a movie fantasy. With their soft cushiony bodies, robots like Baymax have very real prospects as future care-givers, space-travellers and more. Robohub’s Helmut Hauser spoke to the man who inspired Baymax – Chris Atkeson, Professor of Robotics at Carnegie Mellon University – about the hard science behind soft robotics.

[HH] Professor Atkeson, can you give us the background – how Disney approached you and how they decided to use a soft robot for the role of Baymax?

[CA] When Disney makes one of these animation movies, they do research. For example, for the movie Frozen, they had a bunch of animators who were from Southern California and had not really experienced snow. They sent a lot of them to Norway to play in the snow there and film it. That led to the movie Frozen.

For Big Hero 6, they knew they were going make a movie about a robot. They had the outline for the story from a Marvel comic, but they really wanted a robot that was new and different, they didn’t want a Terminator or a Transformer. So they contacted Disney Research, which tours robot laboratories around the world. One of the laboratories they visited was mine. They saw our work on inflatable robots to help dress, people, feed them and comb their hair, and the Disney folks were very happy because they’d found their robot: an inflatable robot that was very, very different from anything that had been in the movies before. And they also found a character for Baymax – a health or personal care, companion robot.

You are working in the field of soft robotics. Could you please explain what that is?

We’d like to have robots help take care of people and trying to do that with a very heavy robot is difficult, because sometimes computers break down or crash and the robot moves in unexpected ways, and sometimes people aren’t very co-operative. When I give a tour of my robotics lab to children, they often try to grab the robot by the legs and [it] could fall down. If a robot is very heavy, let’s say 100-150 kilograms, it can hurt the children or a pet. So I decided the best way to make a robot safe is to make it as light as possible, because mass is what causes gravitational force. Your momentum and your energy are proportional to mass. So, if we can reduce mass, we can reduce force and momentum; we can reduce energy and make it a much safer robot. So I was actually interested in light-weight robots – and maybe that’s what the field should be called – but we ended up deciding that the best way is to make inflatable robots and they’re inherently soft, so we got classified as “soft robotics.”

Can you also talk a little bit about the technological challenges that you have to face when you build inflatable robots?

Many people worry that an inflatable robot is too weak to do anything useful. So, one of the things we tested was: can they lift heavy loads? And yes, they can lift 10 or 15 kilograms and that’s enough for a lot of the care tasks that we want to do. If you don’t use a robot in the configuration of an arm of a humanoid and, instead, put the inflatable part underneath something, you can lift a larger mass. Inflatable devices are used to lift cars and buildings, so they can be very, very strong.

The second fear with inflatable robots is, if you puncture it, it will deflate and be useless. It turns out that the suits used for space walks, on the International Space Station, are also inflatable robots. They’re designed to self-seal if they’re damaged, so they don’t deflate immediately; there are techniques to help inflatable robots survive when they’re punctured, they can have compartments. So, puncturing an inflatable robot is not a big problem. In Big Hero 6, the robot repairs itself after it has several holes in it.

Yes, exactly – with scotch tape.

Yes.

Can you say a little bit more about energy efficiency? Is there a lot of energy needed in order to keep the pressure up in the robot or is that quite easy to do?

I don’t think it’s a lot of energy. It all depends on how much leakage you have. If you have a system that’s continually leaking and inflating, it may run up your energy bill. But if you have a situation where the structure doesn’t leak very much, and you only have to add a little air once in a while, that’s not a big problem.

Lightweight carbon fiber skeleton for an arm. Source: Chris Atkeson

You’ve already talked a little bit about possible applications for such types of robots. Do you have any other applications, outside of care-taking, in mind?

Robots that are toys and interact with children need to be very, very safe so I think soft, or lightweight, robots have an application there. Basically, [in] any kind of situation where you’re interacting with people, we need a high amount of safety.

Do you use any special sensors for your inflatable robots? Maybe a stretchable, bendable sensor, or do you use off-the-shelf sensors?

I think when you have a robot that’s not rigid, you tend to rely more on vision and external sensing. A rigid model can rely on sensors in the joints to achieve accuracy, but with the soft robots, you tend to have to look at where your hand is and where the target is in order to figure out: are you reaching the target accurately?

Closely connected to that, the control approach might be different as well, right? Or do you employ the same techniques that are used for a rigid robot?

I think the control approach may well be different. You can think of it as a much more flexible or complicated dynamic, essentially everything bends. And that means you have to be a little more cautious and use lower “control gains” or “stiffnesses” in order to move the robot around. So I think there need to be slightly different techniques, both in sensing and in control.

Your name is well-known in the field of machine learning too. I was wondering if you have any plans to link your expertise there to soft robots. Do you see the soft body as an advantage there?

We have already used learning for the “kinematics” of the robot; in other words, how to reach accurately, even though the parts of the robot are soft and bendy. The big surprise is that, when you start building complicated metal robots, hard robots, they also bend if they’re complicated enough – like a humanoid robot – because they have so many joints and there is play in them. So some of the techniques that we originally designed for soft robots are actually turning out to be useful for learning with the metal robots.

Baymax concept skeletons. Source: Walt Disney Animation Studios

In the movie, Hero builds rigid body parts for Baymax to enable it to fly around and to fight. Do you think that would make sense in real-life? And, if so, what applications could this have?

I think it’s a very good idea to have robots that can change modes. In this case, Baymax put on a hard outer shell in order to become stiff, and I think that makes a lot of sense. If you have a service or house robot, and it needs to be strong, it could use tools or put on a suit in the same way that people use tools. I think it’s a very cost effective way to get robots to do a wide range of things.

Do you also see a use for such types of robots outside the house, for disaster relief or for military use, for example? Because I would assume that a soft robot doesn’t have to model its environment in order to move around in it. Would that be a good application?

It depends on what kind of disaster you’re imagining. If you have an earthquake, for example, and a lot of rubble, you need small, agile robots to find victims, and very strong robots to dig them out. So maybe we’d have more specialized robots, say, in Japan preparing for an earthquake. If it’s a disaster that involves a lot of people getting sick, like the Ebola situation, then the soft robots may make more sense. They can be made very cheaply because we are using techniques similar to the ones used to make clothes, so we could even have disposable robots rather than trying to clean them. So, in the United States, when the Ebola problem was much greater a few months ago, there was some discussion about what kind of robots we should develop and soft robots was a possible answer.

What about using such types of robots for exo-planetary exploration, since, in space travel, weight and mass are a big issues?

Sure. Did you know we use inflatable landing systems to land probes on Mars? So, that’s already an example. If you’re going to build a habitat that people live in, it would probably be inflatable, if you want to deploy very large structures in space. Currently, we use unfolding wing-like things that are quite complicated. It’s possible that inflating them would be a better way to go – to make very large solar panels or antennas.

Baymax concept. Source: Walt Disney Animation Studios

You have a project called “Build Baymax”. Can you tell us a little bit more about that?

Yes. Of course, it’s inspired by the movie. There are two parts to the project. One is building the body: Can we build something with the capabilities of the robots in the movie? The second part is building the brain: Can we build robots that are capable of having the artificial intelligence that Baymax showed in the movie? We have groups to pursue those two targets, building the body and building the brain.

The movie is – I think – really inspiring, for adults as well as for kids. Because it talks about being a good scientist and being curious about things. So, if you were to give advice to kids who may be interested in soft robotics, what good sources are there for inspiration? What kind of skills does someone need to join the next generation of soft roboticists?

I would, of course, emphasize that studying mathematics and science is very important. But, I also think it’s possible for children to build soft robots, because it’s like making clothes and children can do it at home. If you want to build a metal robot, you typically need access to parts. With soft robots, it’s like building a kite and you can do that in your home. You can have some fun and get some experience. In the United States, we have a term, “home economics,” which is about teaching people to sew and things like that. Soft robotics could make home economics popular again.

Further reading on soft robotics:

Chris Atkeson’s webpage
Build Baymax website
Robosoft – An EU research community around soft robotics

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Every April, National Robotics Week fuels a heightened awareness around robotics, its impact on society, and its growing importance in a wide variety of fields and applications. Robotics, however, never seems to achieve its hyped potential from its beginnings in industrial applications, when the benefits of fast, precise, repetitive manipulation in manufacturing were a significant driver for adoption of early robotics solutions. While robot arms in manufacturing debuted the benefits of robotics technology to industry, the robot arms were put in cages and they largely stayed in those environments.

Today, in contrast, while robot arm sales for manufacturing and other industrial uses are at record highs, new robotic solutions outside of manufacturing are largely dominated by mobile robots: drone planes both large and small, UAV’s, telepresence robots, delivery robots (think Aethon and Savioke), and, of course, mobile vacuum cleaners—today’s all-time robot sales leader.

Manipulation is still a core part of manufacturing, and several employment and demographic issues are developing on a global scale—including the escalation of labor rates, double digit chronic turnover, generational culture changes, and a smaller eligible workforce due to societal aging demographics—that are driving the need for new innovations for manufacturing companies, which I think will have interesting implications for robotics. These innovations are focused on three main areas: low cost, end-effector capability, and dexterity and agile assembly.

Low Cost

The cost of robot arms has dropped significantly over the last decade, as much as 50 percent or more for some applications. Over the last few weeks, two new industrial robot arms were introduced that represent the current bar in the lower cost robot arms race: the UR3 from Universal Robotics at US$23,000, and Sawyer from Rethink Robotics at US$29,000. The story around lower cost robot arms for manufacturing, however, is not as straightforward as lower price equals more uses. Focusing just on price distracts from the practical realities of manufacturing robots. Yes, for every drop in price, there will be some cost-benefit analysis that will justify more use of robots, but this is marginally incremental. Our interaction with manufacturers confirms that the cost of the robot for most current uses is not a limiting factor. The bigger considerations are project and integration costs related to system design, programming, and installation, which account for as much as 80 percent or more of the total cost to deploy.

So when I say low cost, I am talking about a new target—industrial grade robot arms at US$5,000 or less. For manufacturers, this is the price point that would open up a significant broad new set of applications. Our team at SRI has been developing low cost dexterous hands over the last few years. We understand in painstaking detail how quickly the component costs can add up for any dexterous robot. We’ve demonstrated a 12 degree-of-freedom dexterous hand with a bill-of-materials around $500 at volume, and now have our sights on developing an arm that could come in at the $5,000 target price point. However, getting to that solution is hard, given the large parts list and the performance demands on transmissions and motors.

End-effectors

The functionality of a robot arm is determined by its end-effector. An interesting aspect of commercial robot arm companies is that, given this fact, very few of them actually offer their own end-effector products. This makes sense when you consider the wide range of end-effectors that are necessary to handle all of the possible use cases for arms.

In order to extend the capabilities of the current robot arms, there has been a recent surge in new companies developing more capable end-effectors. SRI is contributing to this surge through its spinout, Grabit.  Grabit uses electroadhesion as a novel approach to grasping items—including difficult items such as potato chip bags, textiles, and fresh fruit and vegetables—enabling new capabilities in a cost-effective way while requiring very little power. The thin form factor of Grabit grippers can also increase storage efficiency by stacking items more closely together, and now with EA integrated into conveyor systems, packages can be transported between levels in a mechanically simpler way. Other companies include Robotiq, which has been extending its line of grippers for industrial applications over the last few years, as well as Soft Robotics, Inc., and Empire Robotics, both emerging from different bases of work on soft robotic from Harvard and iRobot.

We have yet to see a fully dexterous robot hand emerge at a price point that can serve a mass market, but I believe this is within reach. We should expect to see more innovation around robot end-effectors.

Dexterity and Agile Assembly

Manufacturers are targeting a next set of robot capabilities related to dexterous assembly and other tasks that are now only possible with the touch of the human hand. A good example of this is the each-pick task, i.e., the ability to reach into a bin of unstructured parts, identify one item, grasp one item, remove one item, and then reposition it for assembly into the part. While today there is no general purpose solution to this problem, there is considerable R&D in universities, startup companies, and in industry to come up with this solution.

For each pick, so far, limited success has been achieved from approaches that use multiple robots to perform sorting in stages that ultimately present parts in a uniform way to the assembly station. It is likely that the eventual solution for each-pick will somehow combine physical dexterity and sensing from new end-effectors with perception and planning.

The Near Future

I’ve described the current R&D target for robotics being driven by the manufacturing market: low-cost, high-performance robots, with end-effectors capable of dexterous manipulation and agile assembly. Considerable investment is being made to create robust solutions, justified by real business drivers affecting the manufacturing industry, which I think will be available within five years or so.

This is opportune timing, based on another big trend I see emerging. As an independent R&D organization, the SRI Robotics Program is working at the leading edge of robotics across emerging service robotics markets like agriculture, elder care, and consumer home products. Whereas robot arm solutions in manufacturing 40 years ago were largely caged inside that industry, this new set of solutions targeted by the manufacturing industry will provide a set of tools that will accelerate deployment of robot arm solutions for these service robot applications and more. For instance, the agricultural industry can look to robotics solutions to help alleviate farmers’ challenges in finding the labor they’ve traditionally used to harvest their crops. There are potential applications in the service industry for performing manual tasks in restaurants such as cleaning and even food preparation. And in the healthcare field, the emergence of low cost robotics can also bring about solutions for therapy, rehabilitation, and personal care applications. It will be exciting to see if it plays out this way.

At SRI, we’re looking forward to enabling a new generation of low cost dexterous manipulation solutions that will drive adoption beyond mobility and beyond manufacturing. Also, this year, we’re once again partnering with Xconomy to host Robo Madness West. Join us along with some of the nation’s leaders in robotics technology and business to take a deep look at the real progress that robots are making today.

This post originally appeared on SRI International. 

image: Soft Robotics Toolkit

In this podcast, Ron Vanderkley speaks to Donal Holland of Harvard University about his team’s work on the Soft Robotics Toolkit.

Soft Robotics is a class of elastically soft, versatile, and biologically inspired machines represents an exciting and highly interdisciplinary paradigm in engineering that could revolutionize the role of robotics in healthcare, field exploration, and cooperative human assistance.

The Soft Robotics Toolkit is a collection of shared resources to support the design, fabrication, modelling, characterization, and control of soft robotic devices. The toolkit was developed as part of educational research being undertaken in the Harvard Biodesign Lab. The ultimate aim of the toolkit is to advance the field of soft robotics by allowing designers and researchers to build upon each other’s work. The web site contains the open source fluidic control board, detailed design for wide range soft robotic components (including actuators and sensors).

https://www.youtube.com/watch?v=67qhphkkibo

The growing popularity of site is now bringing in hobbyist and makers alike. The Soft Robotics Toolkit team has announced two competitions intended to reward students, researchers, makers, and designers of all levels for their contributions to the field of soft robotics.

Donal Holland

Donal Holland is a visiting Lecturer in Engineering Sciences at Harvard School of Engineering and Applied Sciences Demographic info Ireland | Mechanical or Industrial Engineering. He was a passed PhD Student at Trinity College Dublin, Visiting Fellow at Harvard School of Engineering and Applied Sciences, Research Assistant at Treocht Ltd.

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Transcript

Ron Vanderkley:  Welcome to the podcast. Can I get you to introduce yourself?

Donal Holland:  My name is Donal Holland and I’m a visiting lecturer at Harvard School of Engineering and Applied Sciences. I’m a mechanical engineer, and I’m one of the developers of the Soft Robotics Toolkit.

Ron Vanderkley:  Can you explain what soft robotics is?

Donal Holland:  When we say soft robotics, we mean robotic systems that are composed partially or entirely from soft, low modulus materials. In plain language this means materials that are very stretchy or those that are flexible or bendy. This is still quite a broad definition, and in our work we mostly focus on actuators and sensors that are composed from fabrics or elastomers, like silicone. That’s what soft robotics means for us.

Ron Vanderkley:  Can you explain what the Soft Robotics Toolkit is?

Donal Holland:  The Soft Robotics Toolkit is an online connection of resources that are related to soft robotics research and development. We intended it to be an intellectual toolkit rather than a physical collection of parts or tools. The toolkit is a website that describes the design, fabrication, modeling and testing of soft robotic components. We currently have documentation for three categories of components on the website, covering actuators, sensors and control hardware. And for each component, the documentation discusses the design of the component, for example, by giving an overview of how it works, discussing the effect of different parameters on its performance and, where appropriate, we provide tutorials on modeling the component in CAD software. It then talks about fabrication in step-by-step tutorials for how to build this yourself, including building materials and where you can order the materials required.

Depending on the component, we also talk about the kind of research that’s been done on it. For example, how we model this mathematically or numerically, or how we carry out testing to understand its performance. It’s said to be very self-contained and to give an overview of how it’s designed, how it’s built, and how it’s used.

We don’t really talk about how we then combine them into full systems; we leave that open ended to the user. We want to see where people will go themselves. But we do provide some case studies of what other people have done using this component.

Ron Vanderkley:  So basically the toolkit has helped students kick start in the field of soft robotics, eliminating the need to join all the dots together?

Donal Holland:  Exactly. We want to help people avoid reinventing the wheel and build upon each other’s work so that we can move soft robotics forward at a faster pace.

Ron Vanderkley:  As you pointed out, it’s being developed as an academic tool. Has the up tide meant that now there are a whole bunch of other types of users that are very interested in developing their interest in soft robotics?

Donal Holland:  That’s absolutely the case. Originally our goal for the toolkit was for it to be an educational resource for use in our classrooms. We teach some design courses and we want to develop resources that could be useful for our students. So we carried out research to understand what our students’ learning needs were, and then we developed an initial version of the documentation and tested it with a range of undergraduate students just to ensure that it was clear enough that they could understand it.

Next we used the results from these tests to improve the documentation, and then we used it in our own design courses for two years. We usee the feedback from these tests and from our own students to further improve the website, and then in September 2014 we launched it to the public.

While our initial goal was to develop a classroom resource, we also realized along the way that the website could serve a broader educational purpose. For example, soft robotics is a very multi-disciplinary field. We have chemists, mechanical engineers, biologists, electronic and computer engineers all coming together, bringing their own expertise together to develop new systems. The toolkit is a way for these different disciplines to share their knowledge and educate each other so that the field can move along at a faster pace. We’ve also had a lot of interest from high school and middle school teachers and students who would like to use it in their classrooms. There’s a big and active hobbyist community around robotics and Makers in general, and we’ve had a lot of interest from people in those communities as well.

Since launching it’s become a lot broader than we originally intended it, and we’re very excited to see where it goes next.

Ron Vanderkley:  As you pointed out, it’s essentially a list of components etc. Has anyone suggested turning it into something someone can actually purchase? Or is it left to the individuals for source material?

Donal Holland:  At the moment it’s very much left to the individual, but we have had a lot of people suggest or ask if they can buy it. It’s not something we’ve done yet but we’d definitely be open to bringing the components together to make it easier for users in the future. I think one of the big challenges, especially when you’re doing this internationally, is that what might be easy to obtain in one country is almost impossible in another – that’s something that we’re really running up against when we’re working with people around the world.

Ron Vanderkley: I was wondering about how to come up with some of the components in this part of the world …

Donal Holland: I had that experience myself when I lived in Europe, and there’s a lot of really good open source, open design projects out … there but a lot of the time they are based in the US and trying to find the same components in Europe is very difficult. I understand the frustration that people have when they’re trying to do that, so as an interim step we’re very keen to work with people in other countries to find local suppliers that could do equivalent parts. For example, we’re working with some educators in Brazil who are sourcing parts in their own country that we will then put up on the website. We are very open if anyone in any part of the world is interested in contributing lists of local suppliers – we’d love to host that on the website to make it easier for people to be involved.

Ron Vanderkley:  What were the challenges in creating the kit?

Donal Holland:  One of the big difficulties with sharing this type of information – where you’re trying to take expert’s knowledge and share it with other people – is the problem of tacit knowledge. People who are very familiar with a particular field or technology or fabrication method typically have a lot of knowledge that it’s very difficult to make explicit. They often don’t know that they know themselves, if that makes sense. And so it can be difficult for experts to document their knowledge in a way that’s sufficiently clear for non-experts to understand.

Put in another way, an expert has forgotten what it’s like to not be an expert, so it’s difficult for them to educate other people sometimes. Our way of getting around this has been to observe interactions between students and experts and to record a knowledge that is shared. The great thing about these interactions is that the experts have to try to explain their knowledge to a beginner and the beginner is able to ask questions about anything they don’t understand.

That’s really useful for our purposes, and it’s how we overcame that difficulty when we were creating the tool kit.

The next big difficulty that we have is for this to really be useful and sustainable … We need to encourage experts from all around the world to share their knowledge. We want this to be much bigger than ourselves and we see this as a community resource – not our own website. We’re trying to figure out a way to incentivize people to be involved to contribute their knowledge and to stay involved.

Ron Vanderkley:  Are there example projects that are being created that students can actually take a look at, or get inspired from?

Donal Holland:  The toolkit focuses very much on the basic components, which can then be combined to create new devices and systems. By focusing on the fundamental building blocks and keeping it open ended, we hope that more people can take it places that we never would have thought of. To encourage this we’re currently holding a soft robotics design competition, where we’re asking website users, including students and hobbyists, to create something using materials on the website and then to document their designs. Then in July we’ll announce the best designs, share them on the website, and the designers will receive cash prizes. The documented designs will act as examples of what people can do with the toolkits that students can learn from.

Ron Vanderkley:  What is the future of the Soft Robotics Toolkit? Has someone set a timeline? Is it just going to run almost by itself?

Donal Holland:  Ideally, we would like it to get to a stage where it could run by itself. I think right now we’re still very much figuring out what the future of the toolkit is. It’s only really been a few months since we launched to the public and we’re still basically collecting feedback from people to figure out what would be most useful for the soft robotics community, what would be most useful for the maker community, and of course what would be most useful for students. We’ll use that feedback to try and figure out where we go next. But I do think a big part of it is trying to make it more of a community resource and people who are outside the original development team taking over responsibility for parts of the website and making it their own.

Ron Vanderkley:  What is the future soft robotics? Where will it go? Specifically, I noticed that the whole kit is dependent on quite a large environment. Has anyone looked at miniaturizing it and tethering it from the rig?

Donal Holland:  That’s a great question.

In terms of the future of soft robotics, I think there’s a lot of excitement about the field … so I’m really interested to see what the near future is going to hold. Our main interest is in medical applications – most of the research we do is related to the medical applications of soft robotics – and there are already some very nice soft robotic medical devices on the market. That’s one very interesting area that’s definitely going to continue over the next few years. Another area that’s receiving a lot of attention is industrial applications, so in particular end effectors for grasping will definitely continue to grow. In both these situations I think it’s okay to be tethered. For example, if you’re on an industrial robot with a large robotic arm, I think it’s okay to have a fairly large pump that you can be tethered to. You don’t need to be too mobile.

In terms of research applications, a very exciting area right now is biomimetic robotics. There’s a lot of really cool work being done on robots that imitates biological forms – especially animals. One of the reasons this is so interesting is that, on the one hand, roboticists are learning from biologists and are making better robotic systems as a result. And on the other hand, I think robotics research can potentially lead to a better understanding of biological systems. But this is an area where making things untethered becomes very important … for example people building autonomous swimming robots. There’s some pretty good work being done in Daniela Rus’ group at MIT in this area; they have completely un-tethered fish robots that can swim around without being attached to a big rig. This is the area where untethered systems are really going to come from, and there’s going to be some really interesting research done in the next few years.

Ron Vanderkley:  I noticed that they had an example of a combustion system that uses gases to generate thrust. Is that just another up and coming example of where soft robotics can go?

Donal Holland:  This is an area I haven’t been involved with really. The documentation for that project came from ETH, which is great – we are delighted to have contributions coming from outside, and that was our first contribution. There is some work being done at Harvard in that area. I think it’s really interesting because in typical pneumatic systems, the actuation time is quite slow and in our applications, which are often medical, we’re not really bothered because speed isn’t that important – what’s more important is that you’re not doing any damage.

But for biomimetic forms, if you want to have a robot that can jump for example, then you want to be able to do much faster actuation … and that’s where combustion becomes really, really interesting. Again, I think that’s where the biomimetic robotics is really pushing the boundaries of soft robotics actuations. It’s definitely something to keep an eye on and see what’s going to come out that area in the next few years.

Ron Vanderkley:  Should we be looking at the Harvard lab for their next steps, or are there other organizations also moving as rapidly as Harvard?

Donal Holland:  I think there are a lot of groups doing really good stuff around the US, almost too many to list. There’s a lot of really great work at MIT, Carnegie Mellon, at Cornell, a lot of interesting wearable stuff going on at Stanford, in ASU. Around Europe there’s of course the RoboSoft CA that are coordinating a lot of the soft robotics research in Europe and further afield. So it’s hard to try and list off the groups here because there’s just so many it’s really grown in the last few years.

Ten years ago it was a very small handful of researchers mostly in Japan – I should mention there’s a lot of really great work going on in Japan as well. But ten years ago it was mostly a small number of Japanese research groups and now suddenly it’s very much exploded and all over the world there are so many people doing really great work. I work in the bio design lab at Harvard with Professor Connor Walsh, and in terms of our immediate interest, I think wearable robotics is the area that we’re really interested in, but there are a lot of other groups at Harvard as well who are doing really good research, ranging from biomimetic systems to different types of medical devices.

Ron Vanderkley:  Thank you Dolan for your time. We’re excited to see what happens with the competition!

Donal Holland:  Thank you very much for having me. We’d be delighted to hear from any of your listeners with any feedback or thoughts on the toolkit.

All audio interviews are transcribed and edited for clarity. However, we can not assume any responsibility for their accuracy.

Sensory-Motor Tissues for Soft Robots

In this video, PhD student at LIS, EPFL and NCCR Robotics Jun Shintake explains his project “Sensory-Motor tissues for Soft Robots”.

For more information on this project please see:

The project’s website

New soft antagonistic actuator enables robots to fold

A foldable antagonistic actuator (academic paper)

Variable stiffness material based on rigid low-melting-point-alloy microstructures embedded in soft poly(dimethylsiloxane) (PDMS) (academic paper)

Transcript 

Andra: I’m talking today with Soft Robotics CEO, Carl Vause. Can you tell us about your work?

Carl: Our expertise is in the soft actuator, where we are able to make robotic actuators of completely elastomeric material – rubber, silicon rubbers, polyurethanes. It’s a really different aspect of making what you’re normally used to … rigid manipulators, or parallel bar linkages, or linear actuators … but we’re really doing it without any rigid components.

Andra: And what research has this come out of?

Carl: The company was actually spun out of Harvard.

In 2007 there was a DARPA project called ChemBots and Harvard was an awardee on that project. Professor George Whitesides in the chemistry department actually took up the challenge… [which was to] build an octopus. And instead of trying to build a mechatronic robot that we’re all familiar with, they developed the soft actuator … trying to replicate the tentacle. Out of that came the intellectual property that is called ‘pneumatic networks’ – and using pneumatic networks you can build all kinds of different actuators to make fingers, hands, joints and the like.

Harvard worked on this for about five to six years, and then there was a decision that the technology had matured to the point where it was no longer in the best interest to continue research. [Instead they began] commercializing the technology and using it to solve some well-understood problems, and so the company was put together in the late spring/early summer of 2013.

Andra: What are some of the problems and specific applications that you are looking at for Soft Robotics?

Carl: One of the things that’s really interesting about the technology is that it’s low cost, it’s conformal, and you can design the hands in an open loop system to apply just the right amount of force.

The example I use is picking a tomato off of a vine. This would be a very, very difficult problem for a traditional robotic manipulator to do with closed-loop feedback. We can design a soft hand with elastomeric fingers that will only operate at a force that is below the crush force of a tomato. And so you just simply visualize a tomato, you activate the gripper, and it will grab the tomato and pull it.

This really opens up what I like to think of as the future of robotics into collaborative robotics: having robotics being able to work side by side with people and factories, handing instruments and tools to workers on assembly lines … or automating areas that we haven’t been able to automate until now, such as produce processing and food processing. Right now it’s very hard to handle fruits and vegetables with robots, but we really feel that soft robotics will unlock this capability.

Andra: You’ve mentioned collaborative robotics – the ability to safely work alongside people – as one of the significant benefits. And you also mention the opening up new areas, for example handling food and agricultural products. Do you think this will also apply to some of the other areas that have not been so easy for robotic manipulation, like fabrics, textiles, other deformable materials?

Carl: Absolutely I do.

One of the big challenges in robotics is how do you handle these soft things. If you’re shipping a shirt from the shirt manufacturer to an outlet like The Gap, they come folded in a plastic wrap. Picking up a folded shirt in a plastic wrap is very difficult for a robotic manipulator, but we’ve actually shown [we can] handle these delicate highly unstructured objects, and we can do it with a lower complexity than is typically done today. And that same grasper we demonstrated handling a folded shirt can also pick up a bag of rice, or things as varied as children’s toys.

Andra: I find soft robotics a very interesting area because of these wide applications, but naturally there are some limitations as well. I assume there are tradeoffs in accuracy or perhaps in strength. Where do you feel the boundaries of the applications are?

Carl: The biggest feedback we get right now is lifespan.

Traditionally in the research environment, soft robotic devices have not had the best lifespan – they’ve had very low cycles – and if you are talking about automating things such as textile handling, produce handling or collaborative robotics, you need to have cyclic lifetimes that are similar to traditional hard graspers. This is a problem that we’ve really focused on solving, and right now in our lab we have one of our soft manipulators running on a lifetime test. As of this morning we are approaching three million cycles, so we feel like we’ve really bridged that lifecycle/lifetime problem that some soft robotics technologies have had.

The other challenge we have had and are working to address is speed of grasp. Sometimes in soft robotics you’re moving a fluid – whether it’s pneumatic or hydraulic – and it’s obviously at a slower rate than with an electrical motor. But we’ve also demonstrated grasp times in the hundred millisecond range. We feel that the current limitations are well known, but that they can be solved and that solving them is deterministic.

Andra: Are there some advantages as well, in terms of the cost and power-to-weight ratios?

Carl: Absolutely.

Right now we have a small gripper – a light-payload gripper – that can handle about 600 grams reliably. But it weighs only 100 grams, so when you put it on the end of a 1kg arm, you’ve got quite a bit more payload than a traditional device where you’re looking at maybe half of your end-of-arm payload taken up by the weight of the end-effector. We’re able to create very lightweight end-effectors, which make can collaborative arms much more productive in terms of payload capacity.

The other advantage that’s really been a powerful part of soft robotics is the cost. All of our cost goes into the engineering of the devices, but once we can get manufacturing a device, it’s really composed of proprietary design of the actuators, and then a light material such as polycarbonate and silicon elastomers. We’re not talking about an end-effector that’s got a lot of sensors and stepper motor and linkages in it. We believe that the standard cost for an adaptable end-effector can come down in price by an order of magnitude very easily, which is really important to opening up this new market of collaborative robotics.

Andra: You’re having to create a startup that’s going into unchartered waters, and I’m hoping you can tell me a little bit about the process. Soft Robotics has been in existence as a company for just over one year?

Carl: Since July of 2013.

Andra: How many people are there on your team?

Carl: Right now there are five of us. Two fulltime engineers, myself, and we use two consultants to keep the books and take care of our regulatory responsibilities.

Andra: Your background is not in robotics research so much as in business, and you’ve been doing medical devices before this. How did you come to join Soft Robotics?

Carl: My undergraduate degree was in electrical engineering and I worked on doing stepper motor control with 8-bit micro controllers. We were running assembly language at the time, and it was very miserable. I had forgotten all about that and was spending a lot of time with medical devices. I was introduced to [soft robotics] technology, and we were looking at various medical applications for it because of its soft conformal nature, obviously. The thing that makes soft robotics fantastic for handling tomatoes also makes it fantastic for handling human organs.

But when we got started, I remembered all the difficulties I had with control systems and feedback loops, and realized that we had a soft open-loop manipulator technology and that we should really spend time with the robotics community. And once we sat down with the robotics community, [their] feedback was, “This is the kind of thing we’ve had been waiting for! We’ve been trying to make the human hand, and that’s a very costly endeavor that takes a long time and a lot of effort … and you’ve created this highly dexterous, conformal, lightweight device in a short period of time!” With that initial feedback we decided to put all of our major efforts into focusing on the robotics opportunity.

Andra: Has this been supported through commercialization grants through the university, through the labs? What’s the process that has taken you this far, and what’s coming next?

Carl: It’s very difficult to run a hardware startup these days. We’re in the days of mobile apps and wonderful online portals that can access billions of people, but hardware startups require people and engineers and time.

We were lucky in that we did get some initial funding through the government, through two DARPA grants. DARPA had seen thetechnology in the university lab and asked us to push it forward. We’ve also been very lucky with angel investors. The company has been funded partially through government grants and the majority through angel investors who have seen the technology, done their fact checking with the robotics community, and who believe that this is something that will change robotics and will be very important going forward.

Andra: What I see is that angels are playing quite an important role in getting robotics startups closer to a large seed round or series A round, and it is a slower process than it is for many other startups. Certainly mobile and apps tend to give the impression of being cheap and easy to get off the ground, and it’s not totally the case. Whereas with hardware, it’s rarely the case that it’s cheap and easy.

Carl: It’s very interesting because in many of the discussions I have with investors, I try to help them understand that we need to buy materials, we need to fabricate things, we need to have access to a machine shop, and these are not things they’re accustomed to hearing from people working on software.

Andra: What do you think is coming up, that you’re facing?

Carl: The biggest obstacle in this is when you’re taking the technology out of university. The universities do very cutting edge early-stage research, and they’re not concerned about things like cost and manufacturability and scalability of a business process. That is what we spent the first nine months working on: could we get a good design space where we could build soft robotics in a 3D CAD system. That required a lot of work by our engineers. Second, we had to find vendors who could help us actually manufacture the parts in quantity, so that when we did start engaging companies we could sit down and say, “Look we’ve got a design space, we understand the design variables to solve these problems, and we have a manufacturing house that can make these in lots of 100 and lots of 1000 if desired.” That was a good nine months at the beginning of the company.

Now it’s really about understanding what the most important problem to solve is. We can do a lot of things with the soft gripper, and we’ve had suggestions for manipulating chickens and poultry processing, which is very interesting, but I know very little about poultry processing.

So we’ve been engaging the integrators, the end-users, and the robotics companies to really understand what problems they would like to see solved.

To circle back, the dominant themes really are realizing that dream of collaborative robotics, and automating industries (or parts of industries) that haven’t been conducive to robotics yet. But the feedback is, with soft robotics we could really bring automation to those new markets.

Andra: Are you going to tackle this one market at a time? For example, prove one out, and the add another? Or prove one out and then add ten or a hundred others?

Carl: I would say there’s maybe a third way.

What I’d like to do is to prove one out, focus on one market and really show that we can make a difference and then use the technology to go into new markets. And as early stage startup, focus really is important to our success.

As we are proving out these ‘one’ markets, one of the things we’ve been focused on is the unstructured warehousing environment: the ability to pack something that comes in a small electronics box, such as a phone or a tablet, or that shirt that’s wrapped in cellophane, or a football. Manipulating all these with the same system is very challenging and that’s a problem we believe we can solve.

But in that process, we have found that there are a lot of things that people would like us to focus on. Textiles is a good example, produce is a good example. So to bring it back to your original question, we are focusing on single markets at a time, but as we have focused on making a difference in those, that series processing if you will, we’re learning more that’s allowing us to open up new conversations in new markets.

Andra: What do you think is the single biggest obstacle that you’re facing in terms of startup growth? This could range from recruitment, to tools, to facilities, to funding, to things that I haven’t even thought of mentioning …

Carl: If I were giving advice to someone who’s going to start a robotics startup today, I would have them really spend a lot time on how to fund their company. We were at the Massachusetts Innovation UnConference two weeks ago, where we actually ran a session on funding the hardware startup. Traditional backers, the venture capitalists of the world, would really like to see traction.

Traction is the big word you hear in startups today. That means you have to have a prototype or you have to be running live pilots with potential paying customers or potential business partners. [You need to understand] the path and the funding necessary to get you from a really good idea or core technology, to where you have a pilot running and a customer, so you could stand in front of a venture capitalist and say, “This is real technology, we have solved the scientific risk. We can make it work and we have meaningful customers who are interested in the technology.”

By understanding that that’s the journey you’re going to be required to walk, I think you’re bringing clarity to [your] business plan. Unfortunately the world where you can have really great intellectual property or a great idea and get funding, it’s just becoming more difficult in recent years. So getting to that first customer contact is very, very important.

Andra: I agree, and I think by definition there’s a lot of intellectual property out there, but it’s hard to prove that it has value.

Carl: Yes.

Andra: Unless you have developed traction. I’d actually avoided using that word even though it’s written down in my notes, so thank you for bringing that up. [Laughs.]

Carl: You’re welcome!

Andra: Is there anything that you would like to say that we haven’t covered? Do you have any other tips for startups that you’d like to share?

Carl: Absolutely.

There are three things about doing a robotics startup today that I think are very important. One is, everyone is fascinated by robotics, and so whenever I’m out somewhere and someone hears the word robotics, they’re very interested in what we’re doing.

But as we’ve discussed many times at tradeshows, the public perception of robotics is very different from the reality of robotics, and [so second, you need to help] bridge that gap [by showing] the problems we’re trying to solve today versus the reality.

And third is that when you speak with investors – whether they are potential angel investors, or venture capitalists as investors – you need to help them understand the reality of robotics today, and also the vision of what robotics can be, and how you’re going to help move the industry forward. This is really the key I would say.

If you could remember those three things, you could be very successful in this industry.

Andra: That’s great. Thank you very much for your time. I really enjoyed the discussion!

All interviews are edited with great care for clarity of content, and may not represent the text of the original interview exactly. We can not assume responsibility for their accuracy. 

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

• ShanghAI Lectures 2013, Lecture 5 – Soft Robotics and Bioinspiration I
• New soft ‘antagonistic’ actuator enables robots to fold
•  Startup Series #6: MIT Entreprise Forum VLAB
• Startup Series #5: Rodney Brooks, Steve Cousins & Pioneers Festival
• Robot startup series #4: Chris Anderson at CES 2013
• Robot startup series #3: Elad Inbar & RobotAppStore
•  Robot startup series #2: Bob Christopher
•  Robot startup series #1: Autom and Cory Kidd

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

A new foldable actuator has been successfully used to fly a MAV.

Traditionally, many key robot components (including sensors and actuators) are rigid, and this makes it difficult for researchers and industry to make them truly compliant with their surroundings. It’s with this problem in mind that a team from NCCR Robotics in the Laboratory of Intelligent Systems and the Microsystems for Space Technologies Laboratory both at EPFL in Switzerland have developed a new soft actuator that enables robots to fold.

To use hard actuators requires a complex design and can make the final structure fragile – and this is a problem when developing robots for use in cluttered environments such as search and rescue or surveying. Recent solutions have used shape memory alloys (SMAs), pneumatic actuators and electroactive polymers – each with their own advantages but also with disadvantages.

The actuator uses two DEAs

To get around these issues, the NCCR team placed two stacked or single dielectric elastomer actuators (DEAs) on top of each other in an antagonistic configuration in order to create an actuator that allows bidirectional actuation and passive folding. Each DEA consists of a thin elastomer membrane between two compliant electrodes – the opposing charges on each electrode generate an electrostatic force (Maxwell stress), which squeezes the membrane causing thinning and expansion in the direction of free boundary conditions and therefore results in actuation stretch.

The actuator itself consists of two rigid arms connected via elastic hinges, and two sets of DEAs in an antagonistic configuration. When an electric current is applied to one of the DEAs it creates a biased stress between the two DEAs, thus bending the actuator. What is particularly exciting is that this actuator can be literally bent in half without being damaged in any way .

The actuator can be folded completely in half without being damaged

As a result of this robustness, the team behind the actuator have tested it as an elevon (surface used to control pitch and roll) on a remotely controlled, fixed-wing MAV. The elevons were used successfully for numerous flights, with a hand launch and a ground landing (landing is a particularly dangerous time for hardware). The elevon must sustain an angle during flight, meaning that the aerodynamic force acts on its surface, another a common reason for failure in flying robots. A good correlation found between the control signal and movement of the robot illustrates the high performance of the actuator.

What is particularly striking about this actuator is how simply it can be designed and made. By using this structure without additional mechanical parts, transmission loss is prevented. Further, by using a silicon type elastomer, a fast response speed and good positioning control can be achieved.

Fully foldable machines
The possibilities for this kind of compliant actuator are endless – from handling fragile goods in manufacturing to safe human-robot interactions. Future uses may also enable robots to self-deploy without the need for further actuation, leading to a generation of robots capable of programmable shape change and reconfiguration.

The full paper by Shintake, J., Rosset, S., Schubert, B. E., Floreano, D. and Shea, H.R. will be published in an upcoming edition of IEEE/ASME Transactions on Mechatronics and can be downloaded ahead of printing here.

Guest talk in the ShanghAI Lectures, 2011-11-17

Artificial ontogenetic development has been nicely demonstrated by many computer simulation studies in the past. There are, however, still a number of technical challenges in bringing it to the real world. In this presentation, I will introduce some potential solutions to this challenging problem, solutions that stem from soft robotics research. More specifically, we demonstrate how autonomous construction, autonomous body extension, and autonomous robot climbing locomotion can be achieved by exploiting unconventional soft material such as Hot Melt Adhesives.

The ShanghAI Lectures are a videoconference-based lecture series on Embodied Intelligence, run and organized by Rolf Pfeifer (from 2009 till 2012), Fabio Bonsignorio (since 2013), and me with partners around the world.

http://www.youtube.com/watch?v=NV3wxfJ0gKg

Slides

The ShanghAI Lectures have brought us a treasure trove of guest lectures by experts in robotics. You can find the whole series from 2012 here. Now, we’re bringing you the guest lectures you haven’t yet seen from previous years, starting with the first lectures from 2009 and releasing a new guest lecture every Thursday until all the series are complete. Enjoy!

In this second lecture hosted by the Scuola Superiore S. Anna, Matteo Cianchetti builds on the previous lecture to talk about building soft actuators for soft robots. In Matteo’s lecture, titled “Soft actuator design methods“,  he explains that the devil is in the details, but that it’s possible to build soft actuators by insightfully exploiting the properties of Shape Memory Alloy (SMA). Want to learn how?

Guest Lecture – “Can ‘Synthetic Methodology’ cause a paradigm shift?” by Minoru Asada

In this talk Prof. Minoru Asada from the University of Osaka, in Japan, shows the results and discusses the underlying principles of his research on developmental robotics and the of the psychological development of the basic human cognitive functions in the baby and even in the fetus! This is an iconic example of synthetic methodology application.

How can we simulate the development of a fetus, for example? And above all, can ‘Synthetic Methodology’ really cause a paradigm shift? Watch Asada’s  lecture here:

About the ShanghAI Lectures

While in the classical approach “intelligence” was essentially viewed as information processing taking place in the brain, the more recent insight that interaction with the environment is of central importance is gaining acceptance. This has led to the metaphor of embodiment, i.e., that intelligence is always a property of an entire organism — an idea that has far-reaching implications and often leads to surprising insights, but which has not so far been widely exploited in industry practice.

The ShanghAI Lectures project aims to:

• Build a sustainable community of students and researchers in the area of Embodied Intelligence
• Make education and knowledge on cutting-edge scientific topics accessible to everyone
• Explore novel methods of knowledge transfer
• Overcome the complexity of a multi-cultural and interdisciplinary learning context
• Bring global teaching to a new level

These lectures about Natural and Artificial Intelligence have been held via videoconference at the University Carlos III of Madrid in Spain, the University of Zurich in Switzerland, Scuola Superiore Sant’Anna of Pisa, Italy, Humboldt University Berlin in Germany, University of Plymouth and University of Salford in the UK, and 10 other universities around the globe. Students from the participating universities are still working together on the exercises, using Webots by Cyberbotics, and Ludobots by the University of Vermont.

The lectures have also been streamed to allow remote participation to anybody.

The ShanghAI Lectures differ from ‘conventional’ MOOCs as they exploit telecommunication technology to build a global, distributed lecture hall that allows rich interaction rather than simply implementing the good old fashioned TV broadcasting model on a different medium. They also differ from other AI courses as they propose a new paradigm approach to embodied cognition (a.k.a. AI and Robotics). It is a kind of Copernican revolution with respect to GOFAI and its robotics application — and thus a research program for the coming decades.

This year I coordinated the lectures, with help from Prof. Rolf Pfeifer and Dr. Nathan Labhart at the University of Zurich . Rolf Pfeifer and I provided the context (introduction, moderation, and conclusion). As always, there were 2-3  invited guest lectures each week.

Hosted by Prof. Cecilia Laschi from the Scuola Superiore S. Anna in Pisa, Italy, this ShanghAI episode puts together contrasting approaches to ‘embodied intelligence’ and ‘embodied cognition’ in her lecture titled “How an octopus can help build a robot”.

Laschi, who among many other things has coordinated the European ‘Octopus’ project,  shows a radical approach to embodiment starting from the bottom-up, by taking us through the development of the physical soft structure of a robot octopus. Soft robotics has a lot to say about embodied cognition and morphological computation, and also involves several non-trivial engineering challenges. Can building an artificial octopus really help to advance robotics? Don’t miss Cecilia Laschi’s lecture:

Guest Lecture – “From scene segmentation to task based grasping” by Danica Kragic

In this talk Prof. Danica Kragic from the KTH in Stockolm, Sweden shows the benefits of embodiment to grasping – from a top-down approach based on computer vision, machine learning and AI. Kragic has led the Grasp european project, and is a leading researcher in the area of AI and robotics. Whatever DARPA tells you, the problem of grasping still isn’t solved. For example we still don’t have a robot that is able to take the dishes from a real world sink and put them into a dishwasher (this would be a killer application, do you agree?) How long will we have to wait?

A top-down approach to solving ‘real problems’ within the embodied approach to AI and robotics still has several basic research questions to answer. If you have been following the previous lectures you may have noticed that many researchers are approaching the issue of embodied cognition with sometimes very different methods and models, and a synthesis at the level of concrete mathematical models is still missing.

The good news is that we may be on right path. Find out what Kragic has to say on the matter:

Guest Lecture – “Hard Work for Robotics from Soft Actuators” by Bram Vanderborght

Soft robots need soft actuators, and building soft actuators is not a trivial task. Prof. Bram Vanderborght is with the Vrije University Brussels and does cutting-edge research on soft actuators, in particular in legged locomotion of humanoid robots. Dive into the modeling and engineering challenges and subtle solutions presented by Bram Vanderborght in his talk:

About the ShanghAI Lectures

While in the classical approach “intelligence” was essentially viewed as information processing taking place in the brain, the more recent insight that interaction with the environment is of central importance is gaining acceptance. This has led to the metaphor of embodiment, i.e., that intelligence is always a property of an entire organism — an idea that has far-reaching implications and often leads to surprising insights, but which has not so far been widely exploited in industry practice.

The ShanghAI Lectures project aims to:

• Build a sustainable community of students and researchers in the area of Embodied Intelligence
• Make education and knowledge on cutting-edge scientific topics accessible to everyone
• Explore novel methods of knowledge transfer
• Overcome the complexity of a multi-cultural and interdisciplinary learning context
• Bring global teaching to a new level

These lectures about Natural and Artificial Intelligence have been held via videoconference at the University Carlos III of Madrid in Spain, the University of Zurich in Switzerland, Scuola Superiore Sant’Anna of Pisa, Italy, Humboldt University Berlin in Germany, University of Plymouth and University of Salford in the UK, and 10 other universities around the globe. Students from the participating universities are still working together on the exercises, using Webots by Cyberbotics, and Ludobots by the University of Vermont.

The lectures have also been streamed to allow remote participation to anybody.

The ShanghAI Lectures differ from ‘conventional’ MOOCs as they exploit telecommunication technology to build a global, distributed lecture hall that allows rich interaction rather than simply implementing the good old fashioned TV broadcasting model on a different medium. They also differ from other AI courses as they propose a new paradigm approach to embodied cognition (a.k.a. AI and Robotics). It is a kind of Copernican revolution with respect to GOFAI and its robotics application — and thus a research program for the coming decades.

This year I coordinated the lectures, with help from Prof. Rolf Pfeifer and Dr. Nathan Labhart at the University of Zurich . Rolf Pfeifer and I provided the context (introduction, moderation, and conclusion). As always, there were 2-3  invited guest lectures each week.

• Soft Robotics: soft actuation and soft sensing
• Robots with Internal Models, for self-repair
• Self-assembling swarm robots, for adaptive/evolvable morphology
• Autonomous 3D collective robot construction

In this post I want to talk about just the first of these: soft robotics, and why I think we should seriously think about soft robotics in space. Soft robotics – as the name implies – is concerned with making robots soft and compliant. It’s a new discipline that already has its own journal, but not yet a wikipedia page. Soft robots would be soft on the inside as well as the outside – so even the fur-covered Paro robot is not a Soft robot. Soft robotics research is about developing new soft, smart materials for both actuation and sensing (ideally within the same material). Soft robots would have the huge advantage over conventional stiff metal and plastic robots, of being light and, well, soft. For robots designed to interact with humans that’s obviously a huge advantage because it makes the robot intrinsically much safer.

Soft robotics research is still at the exploratory stage, so there are not yet prefered materials and approaches. In our lab we are exploring several avenues, one is electroactive polymers (EAPs) for artificial muscles; another is the bio-mimetic 3D printed flexible artificial whisker. Another approach makes use of shape memory alloys to actuate octopus like limbs: here is a very nice YouTube movie from the EU OCTOPUS project. And perhaps one of the most unlikely but very promising approaches: exploiting fluid-solid phase changes in ground coffee to make a soft gripper: the Jaeger-Lipson coffee balloon gripper.

Let me elaborate a little more on the coffee balloon gripper. Based on the simple observation that when you buy vacuum-packed ground coffee the pack is completely solid, yet as soon as you cut open the pack and release the vacuum the ground coffee returns to its flowing fluid state. Heinrich Jaeger, Hod Lipson and co-workers put ground coffee into a latex balloon then, by controlling the vacuum via a pump, they demonstrate a gripper able to safely pick up and hold more or less any object. Here is a YouTube video showing this remarkable ability.

Almost any planetary exploration robot is likely to need a gripper to pick up or collect rock samples for analysis or collection (for return to Earth). Conventional robot grippers are complex mechanical devices that need very precise control in order to reliably pick up irregularly shaped and sized objects. That control is mechanically and computationally expensive, and problematical because of time delays if it has to be performed remotely from Earth. Something like the Jaeger-Lipson coffee balloon gripper would – I think – provide a much better solution. This soft gripper avoids the hard control and computation because the soft material adapts itself to the thing it is gripping; it’s a great example of what we call morphological computation.

The second example I suggested is inspired by work in our lab on bio-inspired touch sensing. Colleagues have developed a device called TACTIP – a soft flexible touch sensor that provides robots (or robot fingers) with very sensitive touch sensing capable of sensing both shape and texture. Importantly the sensing is done inside TACTIP, so the outside surface of the sensor can sustain damage without loss of sensing. Here is a very nice YouTube report on the TACTIP project.

It’s easy to see that giving planetary robots touch sensing could be useful, but there’s another possibility I outlined: the potential to allow Earth scientists to feel what the robot’s sensor is feeling. PhD student Callum Roke and his co-workers developed a system based on TACTIP for what we call remote tele-haptics. Here is a video clip demonstrating the idea:

Imagine being able to run your fingers across the surface of Mars, or directly feel the texture of a piece of asteroid rock without actually being there.

ETH Zurich’s summer school on Soft Robotics is over. But as of today, you can have a look at the lecture videos and lecture material online!