Tag Archives: complexity

#437992 This Week’s Awesome Tech Stories From ...

Posted on January 23, 2021 by Android

ARTIFICIAL INTELLIGENCE
This Chinese Lab Is Aiming for Big AI Breakthroughs
Will Knight | Wired
“China produces as many artificial intelligence researchers as the US, but it lags in key fields like machine learning. The government hopes to make up ground. …It set AI researchers the goal of making ‘fundamental breakthroughs by 2025’ and called for the country to be ‘the world’s primary innovation center by 2030.’ BAAI opened a year later, in Zhongguancun, a neighborhood of Beijing designed to replicate US innovation hubs such as Boston and Silicon Valley.”

ENVIRONMENT
What Elon Musk’s $100 Million Carbon Capture Prize Could Mean
James Temple | MIT Technology Review
“[Elon Musk] announced on Twitter that he plans to give away $100 million of [his $180 billion net worth] as a prize for the ‘best carbon capture technology.’ …Another $100 million could certainly help whatever venture, or ventures, clinch Musk’s prize. But it’s a tiny fraction of his wealth and will also only go so far. …Money aside, however, one thing Musk has a particular knack for is generating attention. And this is a space in need of it.”

HEALTH
Synthetic Cornea Helped a Legally Blind Man Regain His Sight
Steve Dent | Engadget
“While the implant doesn’t contain any electronics, it could help more people than any robotic eye. ‘After years of hard work, seeing a colleague implant the CorNeat KPro with ease and witnessing a fellow human being regain his sight the following day was electrifying and emotionally moving, there were a lot of tears in the room,’ said CorNeat Vision co-founder Dr. Gilad Litvin.”

BIOTECH
MIT Develops Method for Lab-Grown Plants That May Eventually Lead to Alternatives to Forestry and Farming
Darrell Etherington | TechCrunch
“If the work of these researchers can eventually be used to create a way to produce lab-grown wood for use in construction and fabrication in a way that’s scalable and efficient, then there’s tremendous potential in terms of reducing the impact on forestry globally. Eventually, the team even theorizes you could coax the growth of plant-based materials into specific target shapes, so you could also do some of the manufacturing in the lab, by growing a wood table directly for instance.”

AUTOMATION
FAA Approves First Fully Automated Commercial Drone Flights
Andy Pasztor and Katy Stech Ferek | The Wall Street Journal
“US aviation regulators have approved the first fully automated commercial drone flights, granting a small Massachusetts-based company permission to operate drones without hands-on piloting or direct observation by human controllers or observers. …The company’s Scout drones operate under predetermined flight programs and use acoustic technology to detect and avoid drones, birds, and other obstacles.”

SPACE
China’s Surging Private Space Industry Is Out to Challenge the US
Neel V. Patel | MIT Technology Review
“[The Ceres-1] was a commercial rocket—only the second from a Chinese company ever to go into space. And the launch happened less than three years after the company was founded. The achievement is a milestone for China’s fledgling—but rapidly growing—private space industry, an increasingly critical part of the country’s quest to dethrone the US as the world’s preeminent space power.”

CRYPTOCURRENCY
Janet Yellen Will Consider Limiting Use of Cryptocurrency
Timothy B. Lee | Ars Technica
“Cryptocurrencies could come under renewed regulatory scrutiny over the next four years if Janet Yellen, Joe Biden’s pick to lead the Treasury Department, gets her way. During Yellen’s Tuesday confirmation hearing before the Senate Finance Committee, Sen. Maggie Hassan (D-N.H.) asked Yellen about the use of cryptocurrency by terrorists and other criminals. ‘Cryptocurrencies are a particular concern,’ Yellen responded. ‘I think many are used—at least in a transactions sense—mainly for illicit financing.’i”

SCIENCE
Secret Ingredient Found to Power Supernovas
Thomas Lewton | Quanta
“…Only in the last few years, with the growth of supercomputers, have theorists had enough computing power to model massive stars with the complexity needed to achieve explosions. …These new simulations are giving researchers a better understanding of exactly how supernovas have shaped the universe we see today.”

Image Credit: Ricardo Gomez Angel / Unsplash Continue reading →

Posted in Human Robots

#437912 “Boston Dynamics Will Continue to ...

Posted on December 17, 2020 by Android

Last week’s announcement that Hyundai acquired Boston Dynamics from SoftBank left us with a lot of questions. We attempted to answer many of those questions ourselves, which is typically bad practice, but sometimes it’s the only option when news like that breaks.

Fortunately, yesterday we were able to speak with Michael Patrick Perry, vice president of business development at Boston Dynamics, who candidly answered our questions about Boston Dynamics’ new relationship with Hyundai and what the near future has in store.

IEEE Spectrum: Boston Dynamics is worth 1.1 billion dollars! Can you put that valuation into context for us?

Michael Patrick Perry: Since 2018, we’ve shifted to becoming a commercial organization. And that’s included a number of things, like taking our existing technology and bringing it to market for the first time. We’ve gone from zero to 400 Spot robots deployed, building out an ecosystem of software developers, sensor providers, and integrators. With that scale of deployment and looking at the pipeline of opportunities that we have lined up over the next year, I think people have started to believe that this isn’t just a one-off novelty—that there’s actual value that Spot is able to create. Secondly, with some of our efforts in the logistics market, we’re getting really strong signals both with our Pick product and also with some early discussions around Handle’s deployment in warehouses, which we think are going to be transformational for that industry.

So, the thing that’s really exciting is that two years ago, we were talking about this vision, and people said, “Wow, that sounds really cool, let’s see how you do.” And now we have the validation from the market saying both that this is actually useful, and that we’re able to execute. And that’s where I think we’re starting to see belief in the long-term viability of Boston Dynamics, not just as a cutting-edge research shop, but also as a business.

Photo: Boston Dynamics

Boston Dynamics says it has deployed 400 Spot robots, building out an “ecosystem of software developers, sensor providers, and integrators.”

How would you describe Hyundai’s overall vision for the future of robotics, and how do they want Boston Dynamics to fit into that vision?

In the immediate term, Hyundai’s focus is to continue our existing trajectories, with Spot, Handle, and Atlas. They believe in the work that we’ve done so far, and we think that combining with a partner that understands many of the industries in which we’re targeting, whether its manufacturing, construction, or logistics, can help us improve our products. And obviously as we start thinking about producing these robots at scale, Hyundai’s expertise in manufacturing is going to be really helpful for us.

Looking down the line, both Boston Dynamics and Hyundai believe in the value of smart mobility, and they’ve made a number of plays in that space. Whether it’s urban air mobility or autonomous driving, they’ve been really thinking about connecting the digital and the physical world through moving systems, whether that’s a car, a vertical takeoff and landing multi-rotor vehicle, or a robot. We are well positioned to take on robotics side of that while also connecting to some of these other autonomous services.

Can you tell us anything about the kind of robotics that the Hyundai Motor Group has going on right now?

So they’re working on a lot of really interesting stuff—exactly how that connects, you know, it’s early days, and we don’t have anything explicitly to share. But they’ve got a smart and talented robotics team that’s working in a variety of directions that shares overlap with us. Obviously, a lot of things related to autonomous driving shares some DNA with the work that we’re doing in autonomy for Spot and Handle, so it’s pretty exciting to see.

What are you most excited about here? How do you think this deal will benefit Boston Dynamics?

I think there are a number of things. One is that they have an expertise in hardware, in a way that’s unique. They understand and appreciate the complexity of creating large complex robotic systems. So I think there’s some shared understanding of what it takes to create a great hardware product. And then also they have the resources to help us actually build those products with them together—they have manufacturing resources and things like that.

“Robotics isn’t a short term game. We’ve scaled pretty rapidly but if you start looking at what the full potential of a company like Boston Dynamics is, it’s going to take years to realize, and I think Hyundai is committed to that long-term vision”

Another thing that’s exciting is that Hyundai has some pretty visionary bets for autonomous driving and unmanned aerial systems, and all of that fits very neatly into the connected vision of robotics that we were talking about before. Robotics isn’t a short term game. We’ve scaled pretty rapidly for a robotics company in terms of the scale of robots we’ve able to deploy in the field, but if you start looking at what the full potential of a company like Boston Dynamics is, it’s going to take years to realize, and I think Hyundai is committed to that long-term vision.

And when you’ve been talking with Hyundai, what are they most excited about?

I think they’re really excited about our existing products and our technology. Looking at some of the things that Spot, Pick, and Handle are able to do now, there are applications that many of Hyundai’s customers could benefit from in terms of mobility, remote sensing, and material handling. Looking down the line, Hyundai is also very interested in smart city technology, and mobile robotics is going to be a core piece of that.

We tend to focus on Spot and Handle and Atlas in terms of platform capabilities, but can you talk a bit about some of the component-level technology that’s unique to Boston Dynamics, and that could be of interest to Hyundai?

Creating very power-dense actuator design is something that we’ve been successful at for several years, starting back with BigDog and LS3. And Handle has some hydraulic actuators and valves that are pretty unique in terms of their design and capability. Fundamentally, we have a systems engineering approach that brings together both hardware and software internally. You’ll often see different groups that specialize in something, like great mechanical or electrical engineering groups, or great controls teams, but what I think makes Boston Dynamics so special is that we’re able to put everything on the table at once to create a system that’s incredibly capable. And that’s why with something like Spot, we’re able to produce it at scale, while also making it flexible enough for all the different applications that the robot is being used for right now.

It’s hard to talk specifics right now, but there are obviously other disciplines within mechanical engineering or electrical engineering or controls for robots or autonomous systems where some of our technology could be applied.

Photo: Boston Dynamics

Boston Dynamics is in the process of commercializing Handle, iterating on its design and planning to get box-moving robots on-site with customers in the next year or two.

While Boston Dynamics was part of Google, and then SoftBank, it seems like there’s been an effort to maintain independence. Is it going to be different with Hyundai? Will there be more direct integration or collaboration?

Obviously it’s early days, but right now, we have support to continue executing against all the plans that we have. That includes all the commercialization of Spot, as well as things for Atlas, which is really going to be pushing the capability of our team to expand into new areas. That’s going to be our immediate focus, and we don’t see anything that’s going to pull us away from that core focus in the near term.

As it stands right now, Boston Dynamics will continue to be Boston Dynamics under this new ownership.

How much of what you do at Boston Dynamics right now would you characterize as fundamental robotics research, and how much is commercialization? And how do you see that changing over the next couple of years?

We have been expanding our commercial team, but we certainly keep a lot of the core capabilities of fundamental robotics research. Some of it is very visible, like the new behavior development for Atlas where we’re pushing the limits of perception and path planning. But a lot of the stuff that we’re working on is a little bit under the hood, things that are less obvious—terrain handling, intervention handling, how to make safe faults, for example. Initially when Spot started slipping on things, it would flail around trying to get back up. We’ve had to figure out the right balance between the robot struggling to stand, and when it should decide to just lock its limbs and fall over because it’s safer to do that.

I’d say the other big thrust for us is manipulation. Our gripper for Spot is coming out early next year, and that’s going to unlock a new set of capabilities for us. We have years and years of locomotion experience, but the ability to manipulate is a space that’s still relatively new to us. So we’ve been ramping up a lot of work over the last several years trying to get to an early but still valuable iteration of the technology, and we’ll continue pushing on that as we start learning what’s most useful to our customers.

“I’d say the other big thrust for us is manipulation. Our gripper for Spot is coming out early next year, and that’s going to unlock a new set of capabilities for us. We have years and years of locomotion experience, but the ability to manipulate is a space that’s still relatively new to us”

Looking back, Spot as a commercial robot has a history that goes back to robots like LS3 and BigDog, which were very ambitious projects funded by agencies like DARPA without much in the way of commercial expectations. Do you think these very early stage, very expensive, very technical projects are still things that Boston Dynamics can take on?

Yes—I would point to a lot of the things we do with Atlas as an example of that. While we don’t have immediate plans to commercialize Atlas, we can point to technologies that come out of Atlas that have enabled some of our commercial efforts over time. There’s not necessarily a clear roadmap of how every piece of Atlas research is going to feed over into a commercial product; it’s more like, this is a really hard fundamental robotics challenge, so let’s tackle it and learn things that we can then benefit from across the company.

And fundamentally, our team loves doing cool stuff with robots, and you’ll continue seeing that in the months to come.

Photo: Boston Dynamics

Spot’s arm with gripper is coming out early next year, and Boston Dynamics says that’s going to “unlock a new set of capabilities for us.”

What would it take to commercialize Atlas? And are you getting closer with Handle?

We’re in the process of commercializing Handle. We’re at a relatively early stage, but we have a plan to get the first versions for box moving on-site with customers in the next year or two. Last year, we did some on-site deployments as proof-of-concept trials, and using the feedback from that, we did a new design pass on the robot, and we’re looking at increasing our manufacturing capability. That’s all in progress.

For Atlas, it’s like the Formula 1 of robots—you’re not going to take a Formula 1 car and try to make it less capable so that you can drive it on the road. We’re still trying to see what are some applications that would necessitate an energy and computationally intensive humanoid robot as opposed to something that’s more inherently stable. Trying to understand that application space is something that we’re interested in, and then down the line, we could look at creating new morphologies to help address specific applications. In many ways, Handle is the first version of that, where we said, “Atlas is good at moving boxes but it’s very complicated and expensive, so let’s create a simpler and smaller design that can achieve some of the same things.”

The press release mentioned a mobile robot for warehouses that will be introduced next year—is that Handle?

Yes, that’s the work that we’re doing on Handle.

As we start thinking about a whole robotic solution for the warehouse, we have to look beyond a high power, low footprint, dynamic platform like Handle and also consider things that are a little less exciting on video. We need a vision system that can look at a messy stack of boxes and figure out how to pick them up, we need an interface between a robot and an order building system—things where people might question why Boston Dynamics is focusing on them because it doesn’t fit in with our crazy backflipping robots, but it’s really incumbent on us to create that full end-to-end solution.

Are you confident that under Hyundai’s ownership, Boston Dynamics will be able to continue taking the risks required to remain on the cutting edge of robotics?

I think we will continue to push the envelope of what robots are capable of, and I think in the near term, you’ll be able to see that realized in our products and the research that we’re pushing forward with. 2021 is going to be a great year for us. Continue reading →

Posted in Human Robots

#437859 We Can Do Better Than Human-Like Hands ...

Posted on December 2, 2020 by Android

One strategy for designing robots that are capable in anthropomorphic environments is to make the robots themselves as anthropomorphic as possible. It makes sense—for example, there are stairs all over the place because humans have legs, and legs are good at stairs, so if we give robots legs like humans, they’ll be good at stairs too, right? We also see this tendency when it comes to robotic grippers, because robots need to grip things that have been optimized for human hands.

Despite some amazing robotic hands inspired by the biology of our own human hands, there are also opportunities for creativity in gripper designs that do things human hands are not physically capable of. At ICRA 2020, researchers from Stanford University presented a paper on the design of a robotic hand that has fingers made of actuated rollers, allowing it to manipulate objects in ways that would tie your fingers into knots.

While it’s got a couple fingers, this prototype “roller grasper” hand tosses anthropomorphic design out the window in favor of unique methods of in-hand manipulation. The roller grasper does share some features with other grippers designed for in-hand manipulation using active surfaces (like conveyor belts embedded in fingers), but what’s new and exciting here is that those articulated active roller fingertips (or whatever non-anthropomorphic name you want to give them) provide active surfaces that are steerable. This means that the hand can grasp objects and rotate them without having to resort to complex sequences of finger repositioning, which is how humans do it.

Photo: Stanford University

Things like picking something flat off of a table, always tricky for robotic hands (and sometimes for human hands as well), is a breeze thanks to the fingertip rollers.

Each of the hand’s fingers has three actuated degrees of freedom, which result in several different ways in which objects can be grasped and manipulated. Things like picking something flat off of a table, always tricky for robotic hands (and sometimes for human hands as well), is a breeze thanks to the fingertip rollers. The motion of an object in this gripper isn’t quite holonomic, meaning that it can’t arbitrarily reorient things without sometimes going through other intermediate steps. And it’s also not compliant in the way that many other grippers are, limiting some types of grasps. This particular design probably won’t replace every gripper out there, but it’s particularly skilled at some specific kinds of manipulations in a way that makes it unique.

We should be clear that it’s not the intent of this paper (or of this article!) to belittle five-fingered robotic hands—the point is that there are lots of things that you can do with totally different hand designs, and just because humans use one kind of hand doesn’t mean that robots need to do the same if they want to match (or exceed) some specific human capabilities. If we could make robotic hands with five fingers that had all of the actuation and sensing and control that our own hands do, that would be amazing, but it’s probably decades away. In the meantime, there are plenty of different designs to explore.

And speaking of exploring different designs, these same folks are already at work on version two of their hand, which replaces the fingertip rollers with fingertip balls:

For more on this new version of the hand (among other things), we spoke with lead author Shenli Yuan via email. And the ICRA page is here if you have questions of your own.

IEEE Spectrum: Human hands are often seen as the standard for manipulation. When adding degrees of freedom that human hands don’t have (as in your work) can make robotic hands more capable than ours in many ways, do you think we should still think of human hands as something to try and emulate?

Shenli Yuan: Yes, definitely. Not only because human hands have great manipulation capability, but because we’re constantly surrounded by objects that were designed and built specifically to be manipulated by the human hand. Anthropomorphic robot hands are still worth investigating, and still have a long way to go before they truly match the dexterity of a human hand. The design we came up with is an exploration of what unique capabilities may be achieved if we are not bound by the constraints of anthropomorphism, and what a biologically impossible mechanism may achieve in robotic manipulation. In addition, for lots of tasks, it isn’t necessarily optimal to try and emulate the human hand. Perhaps in 20 to 50 years when robot manipulators are much better, they won’t look like the human hand that much. The design constraints for robotics and biology have points in common (like mechanical wear, finite tendons stiffness) but also major differences (like continuous rotation for robots and less heat dissipation problems for humans).

“For lots of tasks, it isn’t necessarily optimal to try and emulate the human hand. Perhaps in 20 to 50 years when robot manipulators are much better, they won’t look like the human hand that much.”
—Shenli Yuan, Stanford University

What are some manipulation capabilities of human hands that are the most difficult to replicate with your system?

There are a few things that come to mind. It cannot perform a power grasp (using the whole hand for grasping as opposed to pinch grasp that uses only fingertips), which is something that can be easily done by human hands. It cannot move or rotate objects instantaneously in arbitrary directions or about arbitrary axes, though the human hand is somewhat limited in this respect as well. It also cannot perform gaiting. That being said, these limitations exist largely because this grasper only has 9 degrees of freedom, as opposed to the human hand which has more than 20. We don’t think of this grasper as a replacement for anthropomorphic hands, but rather as a way to provide unique capabilities without all of the complexity associated with a highly actuated, humanlike hand.

What’s the most surprising or impressive thing that your hand is able to do?

The most impressive feature is that it can rotate objects continuously, which is typically difficult or inefficient for humanlike robot hands. Something really surprising was that we put most of our energy into the design and analysis of the grasper, and the control strategy we implemented for demonstrations is very simple. This simple control strategy works surprisingly well with very little tuning or trial-and-error.

With this many degrees of freedom, how complicated is it to get the hand to do what you want it to do?

The number of degrees of freedom is actually not what makes controlling it difficult. Most of the difficulties we encountered were actually due to the rolling contact between the rollers and the object during manipulation. The rolling behavior can be viewed as constantly breaking and re-establishing contacts between the rollers and objects, this very dynamic behavior introduces uncertainties in controlling our grasper. Specifically, it was difficult estimating the velocity of each contact point with the object, which changes based on object and finger position, object shape (especially curvature), and slip/no slip.

What more can you tell us about Roller Grasper V2?

Roller Grasper V2 has spherical rollers, while the V1 has cylindrical rollers. We realized that cylindrical rollers are very good at manipulating objects when the rollers and the object form line contacts, but it can be unstable when the grasp geometry doesn’t allow for a line contact between each roller and the grasped object. Spherical rollers solve that problem by allowing predictable points of contact regardless of how a surface is oriented.

The parallelogram mechanism of Roller Grasper V1 makes the pivot axis offset a bit from the center of the roller, which made our control and analysis more challenging. The kinematics of the Roller Grasper V2 is simpler. The base joint intersects with the finger, which intersects with the pivot joint, and the pivot joint intersects with the roller joint. It’s symmetrical design and simpler kinematics make our control and analysis a lot more straightforward. Roller Grasper V2 also has a larger pivot range of 180 degrees, while V1 is limited to 90 degrees.

In terms of control, we implemented more sophisticated control strategies (including a hand-crafted control strategy and an imitation learning based strategy) for the grasper to perform autonomous in-hand manipulation.

“Design of a Roller-Based Dexterous Hand for Object Grasping and Within-Hand Manipulation,” by Shenli Yuan, Austin D. Epps, Jerome B. Nowak, and J. Kenneth Salisbury from Stanford University is being presented at ICRA 2020.

< Back to IEEE Journal Watch Continue reading →

Posted in Human Robots

#437816 As Algorithms Take Over More of the ...

Posted on December 1, 2020 by Android

Algorithms play an increasingly prominent part in our lives, governing everything from the news we see to the products we buy. As they proliferate, experts say, we need to make sure they don’t collude against us in damaging ways.

Fears of malevolent artificial intelligence plotting humanity’s downfall are a staple of science fiction. But there are plenty of nearer-term situations in which relatively dumb algorithms could do serious harm unintentionally, particularly when they are interlocked in complex networks of relationships.

In the economic sphere a high proportion of decision-making is already being offloaded to machines, and there have been warning signs of where that could lead if we’re not careful. The 2010 “Flash Crash,” where algorithmic traders helped wipe nearly $1 trillion off the stock market in minutes, is a textbook example, and widespread use of automated trading software has been blamed for the increasing fragility of markets.

But another important place where algorithms could undermine our economic system is in price-setting. Competitive markets are essential for the smooth functioning of the capitalist system that underpins Western society, which is why countries like the US have strict anti-trust laws that prevent companies from creating monopolies or colluding to build cartels that artificially inflate prices.

These regulations were built for an era when pricing decisions could always be traced back to a human, though. As self-adapting pricing algorithms increasingly decide the value of products and commodities, those laws are starting to look unfit for purpose, say the authors of a paper in Science.

Using algorithms to quickly adjust prices in a dynamic market is not a new idea—airlines have been using them for decades—but previously these algorithms operated based on rules that were hard-coded into them by programmers.

Today the pricing algorithms that underpin many marketplaces, especially online ones, rely on machine learning instead. After being set an overarching goal like maximizing profit, they develop their own strategies based on experience of the market, often with little human oversight. The most advanced also use forms of AI whose workings are opaque even if humans wanted to peer inside.

In addition, the public nature of online markets means that competitors’ prices are available in real time. It’s well-documented that major retailers like Amazon and Walmart are engaged in a never-ending bot war, using automated software to constantly snoop on their rivals’ pricing and inventory.

This combination of factors sets the stage perfectly for AI-powered pricing algorithms to adopt collusive pricing strategies, say the authors. If given free reign to develop their own strategies, multiple pricing algorithms with real-time access to each other’s prices could quickly learn that cooperating with each other is the best way to maximize profits.

The authors note that researchers have already found evidence that pricing algorithms will spontaneously develop collusive strategies in computer-simulated markets, and a recent study found evidence that suggests pricing algorithms may be colluding in Germany’s retail gasoline market. And that’s a problem, because today’s anti-trust laws are ill-suited to prosecuting this kind of behavior.

Collusion among humans typically involves companies communicating with each other to agree on a strategy that pushes prices above the true market value. They then develop rules to determine how they maintain this markup in a dynamic market that also incorporates the threat of retaliatory pricing to spark a price war if another cartel member tries to undercut the agreed pricing strategy.

Because of the complexity of working out whether specific pricing strategies or prices are the result of collusion, prosecutions have instead relied on communication between companies to establish guilt. That’s a problem because algorithms don’t need to communicate to collude, and as a result there are few legal mechanisms to prosecute this kind of collusion.

That means legal scholars, computer scientists, economists, and policymakers must come together to find new ways to uncover, prohibit, and prosecute the collusive rules that underpin this behavior, say the authors. Key to this will be auditing and testing pricing algorithms, looking for things like retaliatory pricing, price matching, and aggressive responses to price drops but not price rises.

Once collusive pricing rules are uncovered, computer scientists need to come up with ways to constrain algorithms from adopting them without sacrificing their clear efficiency benefits. It could also be helpful to make preventing this kind of collusive behavior the responsibility of the companies deploying them, with stiff penalties for those who don’t keep their algorithms in check.

One problem, though, is that algorithms may evolve strategies that humans would never think of, which could make spotting this behavior tricky. Imbuing courts with the technical knowledge and capacity to investigate this kind of evidence will also prove difficult, but getting to grips with these problems is an even more pressing challenge than it might seem at first.

While anti-competitive pricing algorithms could wreak havoc, there are plenty of other arenas where collusive AI could have even more insidious effects, from military applications to healthcare and insurance. Developing the capacity to predict and prevent AI scheming against us will likely be crucial going forward.

Image Credit: Pexels from Pixabay Continue reading →

Posted in Human Robots

#437800 Malleable Structure Makes Robot Arm More ...

Posted on November 30, 2020 by Android

The majority of robot arms are built out of some combination of long straight tubes and actuated joints. This isn’t surprising, since our limbs are built the same way, which was a clever and efficient bit of design. By adding more tubes and joints (or degrees of freedom), you can increase the versatility of your robot arm, but the tradeoff is that complexity, weight, and cost will increase, too.

At ICRA, researchers from Imperial College London’s REDS Lab, headed by Nicolas Rojas, introduced a design for a robot that’s built around a malleable structure rather than a rigid one, allowing you to improve how versatile the arm is without having to add extra degrees of freedom. The idea is that you’re no longer constrained to static tubes and joints but can instead reconfigure your robot to set it up exactly the way you want and easily change it whenever you feel like.

Inside of that bendable section of arm are layers and layers of mylar sheets, cut into flaps and stacked on top of one another so that each flap is overlapping or overlapped by at least 11 other flaps. The mylar is slippery enough that under most circumstances, the flaps can move smoothly against each other, letting you adjust the shape of the arm. The flaps are sealed up between latex membranes, and when air is pumped out from between the membranes, they press down on each other and turn the whole structure rigid, locking itself in whatever shape you’ve put it in.

Image: Imperial College London

The malleable part of the robot consists of layers of mylar sheets, cut into flaps that can move smoothly against each other, letting you adjust the shape of the arm. The flaps are sealed up between latex membranes, and when air is pumped out from between the membranes, they press down on each other and turn the whole structure rigid, locking itself in whatever shape you’ve put it in.

The nice thing about this system is that it’s a sort of combination of a soft robot and a rigid robot—you get the flexibility (both physical and metaphorical) of a soft system, without necessarily having to deal with all of the control problems. It’s more mechanically complex than either (as hybrid systems tend to be), but you save on cost, size, and weight, and reduce the number of actuators you need, which tend to be points of failure. You do need to deal with creating and maintaining a vacuum, and the fact that the malleable arm is not totally rigid, but depending on your application, those tradeoffs could easily be worth it.

For more details, we spoke with first author Angus B. Clark via email.

IEEE Spectrum: Where did this idea come from?

Angus Clark: The idea of malleable robots came from the realization that the majority of serial robot arms have 6 or more degrees of freedom (DoF)—usually rotary joints—yet are typically performing tasks that only require 2 or 3 DoF. The idea of a robot arm that achieves flexibility and adaptation to tasks but maintains the simplicity of a low DoF system, along with the rapid development of variable stiffness continuum robots for medical applications, inspired us to develop the malleable robot concept.

What are some ways in which a malleable robot arm could provide unique advantages, and what are some potential applications that could leverage these advantages?

Malleable robots have the ability to complete multiple traditional tasks, such as pick and place or bin picking operations, without the added bulk of extra joints that are not directly used within each task, as the flexibility of the robot arm is provided by ​a malleable link instead. This results in an overall smaller form factor, including weight and footprint of the robot, as well as a lower power requirement and cost of the robot as fewer joints are needed, without sacrificing adaptability. This makes the robot ideal for scenarios where any of these factors are critical, such as in space robotics—where every kilogram saved is vital—or in rehabilitation robotics, where cost reduction may facilitate adoption, to name two examples. Moreover, the collaborative soft-robot-esque nature of malleable robots also tends towards collaborative robots in factories working safely alongside and with humans.

“The idea of malleable robots came from the realization that the majority of serial robot arms have 6 or more degrees of freedom (DoF), yet are typically performing tasks that only require 2 or 3 DoF”
—Angus B. Clark, Imperial College London

Compared to a conventional rigid link between joints, what are the disadvantages of using a malleable link?

Currently the maximum stiffness of a malleable link is considerably weaker than that of an equivalent solid steel rigid link, and this is one of the key areas we are focusing research on improving as motion precision and accuracy are impacted. We have created the largest existing variable stiffness link at roughly 800 mm length and 50 mm diameter, which suits malleable robots towards small and medium size workspaces. Our current results evaluating this accuracy are good, however achieving a uniform stiffness across the entire malleable link can be problematic due to the production of wrinkles under bending in the encapsulating membrane. As demonstrated by our SCARA topology results, this can produce slight structural variations resulting in reduced accuracy.

Does the robot have any way of knowing its own shape? Potentially, could this system reconfigure itself somehow?

Currently we compute the robot topology using motion tracking, with markers placed on the joints of the robot. Using distance geometry, we are then able to obtain the forward and inverse kinematics of the robot, of which we can use to control the end effector (the gripper) of the robot. Ideally, in the future we would love to develop a system that no longer requires the use of motion tracking cameras.

As for the robot reconfiguring itself, which we call an “intrinsic malleable link,” there are many methods that have been demonstrated for controlling a continuum structure, such as using positive pressure or via tendon wires, however the ability to in real-time determine the curvature of the link, not just the joint positions, is a significant hurdle to solve. However, we hope to see future development on malleable robots work towards solving this problem.

What are you working on next?

For us, refining the kinematics of the robot to enable a robust and complete system for allowing a user to collaboratively reshape the robot, while still achieving the accuracy expected from robotic systems, is our current main goal. Malleable robots are a brand new field we have introduced, and as such provide many opportunities for development and optimization. Over the coming years, we hope to see other researchers work alongside us to solve these problems.

“Design and Workspace Characterization of Malleable Robots,” by Angus B. Clark and Nicolas Rojas from Imperial College London, was presented at ICRA 2020.

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