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#437929 These Were Our Favorite Tech Stories ...
This time last year we were commemorating the end of a decade and looking ahead to the next one. Enter the year that felt like a decade all by itself: 2020. News written in January, the before-times, feels hopelessly out of touch with all that came after. Stories published in the early days of the pandemic are, for the most part, similarly naive.
The year’s news cycle was swift and brutal, ping-ponging from pandemic to extreme social and political tension, whipsawing economies, and natural disasters. Hope. Despair. Loneliness. Grief. Grit. More hope. Another lockdown. It’s been a hell of a year.
Though 2020 was dominated by big, hairy societal change, science and technology took significant steps forward. Researchers singularly focused on the pandemic and collaborated on solutions to a degree never before seen. New technologies converged to deliver vaccines in record time. The dark side of tech, from biased algorithms to the threat of omnipresent surveillance and corporate control of artificial intelligence, continued to rear its head.
Meanwhile, AI showed uncanny command of language, joined Reddit threads, and made inroads into some of science’s grandest challenges. Mars rockets flew for the first time, and a private company delivered astronauts to the International Space Station. Deprived of night life, concerts, and festivals, millions traveled to virtual worlds instead. Anonymous jet packs flew over LA. Mysterious monoliths appeared and disappeared worldwide.
It was all, you know, very 2020. For this year’s (in-no-way-all-encompassing) list of fascinating stories in tech and science, we tried to select those that weren’t totally dated by the news, but rose above it in some way. So, without further ado: This year’s picks.
How Science Beat the Virus
Ed Yong | The Atlantic
“Much like famous initiatives such as the Manhattan Project and the Apollo program, epidemics focus the energies of large groups of scientists. …But ‘nothing in history was even close to the level of pivoting that’s happening right now,’ Madhukar Pai of McGill University told me. … No other disease has been scrutinized so intensely, by so much combined intellect, in so brief a time.”
‘It Will Change Everything’: DeepMind’s AI Makes Gigantic Leap in Solving Protein Structures
Ewen Callaway | Nature
“In some cases, AlphaFold’s structure predictions were indistinguishable from those determined using ‘gold standard’ experimental methods such as X-ray crystallography and, in recent years, cryo-electron microscopy (cryo-EM). AlphaFold might not obviate the need for these laborious and expensive methods—yet—say scientists, but the AI will make it possible to study living things in new ways.”
OpenAI’s Latest Breakthrough Is Astonishingly Powerful, But Still Fighting Its Flaws
James Vincent | The Verge
“What makes GPT-3 amazing, they say, is not that it can tell you that the capital of Paraguay is Asunción (it is) or that 466 times 23.5 is 10,987 (it’s not), but that it’s capable of answering both questions and many more beside simply because it was trained on more data for longer than other programs. If there’s one thing we know that the world is creating more and more of, it’s data and computing power, which means GPT-3’s descendants are only going to get more clever.”
Artificial General Intelligence: Are We Close, and Does It Even Make Sense to Try?
Will Douglas Heaven | MIT Technology Review
“A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. …So why is AGI controversial? Why does it matter? And is it a reckless, misleading dream—or the ultimate goal?”
The Dark Side of Big Tech’s Funding for AI Research
Tom Simonite | Wired
“Timnit Gebru’s exit from Google is a powerful reminder of how thoroughly companies dominate the field, with the biggest computers and the most resources. …[Meredith] Whittaker of AI Now says properly probing the societal effects of AI is fundamentally incompatible with corporate labs. ‘That kind of research that looks at the power and politics of AI is and must be inherently adversarial to the firms that are profiting from this technology.’i”
We’re Not Prepared for the End of Moore’s Law
David Rotman | MIT Technology Review
“Quantum computing, carbon nanotube transistors, even spintronics, are enticing possibilities—but none are obvious replacements for the promise that Gordon Moore first saw in a simple integrated circuit. We need the research investments now to find out, though. Because one prediction is pretty much certain to come true: we’re always going to want more computing power.”
Inside the Race to Build the Best Quantum Computer on Earth
Gideon Lichfield | MIT Technology Review
“Regardless of whether you agree with Google’s position [on ‘quantum supremacy’] or IBM’s, the next goal is clear, Oliver says: to build a quantum computer that can do something useful. …The trouble is that it’s nearly impossible to predict what the first useful task will be, or how big a computer will be needed to perform it.”
The Secretive Company That Might End Privacy as We Know It
Kashmir Hill | The New York Times
“Searching someone by face could become as easy as Googling a name. Strangers would be able to listen in on sensitive conversations, take photos of the participants and know personal secrets. Someone walking down the street would be immediately identifiable—and his or her home address would be only a few clicks away. It would herald the end of public anonymity.”
Wrongfully Accused by an Algorithm
Kashmir Hill | The New York Times
“Mr. Williams knew that he had not committed the crime in question. What he could not have known, as he sat in the interrogation room, is that his case may be the first known account of an American being wrongfully arrested based on a flawed match from a facial recognition algorithm, according to experts on technology and the law.”
Predictive Policing Algorithms Are Racist. They Need to Be Dismantled.
Will Douglas Heaven | MIT Technology Review
“A number of studies have shown that these tools perpetuate systemic racism, and yet we still know very little about how they work, who is using them, and for what purpose. All of this needs to change before a proper reckoning can take pace. Luckily, the tide may be turning.”
The Panopticon Is Already Here
Ross Andersen | The Atlantic
“Artificial intelligence has applications in nearly every human domain, from the instant translation of spoken language to early viral-outbreak detection. But Xi [Jinping] also wants to use AI’s awesome analytical powers to push China to the cutting edge of surveillance. He wants to build an all-seeing digital system of social control, patrolled by precog algorithms that identify potential dissenters in real time.”
The Case For Cities That Aren’t Dystopian Surveillance States
Cory Doctorow | The Guardian
“Imagine a human-centered smart city that knows everything it can about things. It knows how many seats are free on every bus, it knows how busy every road is, it knows where there are short-hire bikes available and where there are potholes. …What it doesn’t know is anything about individuals in the city.”
The Modern World Has Finally Become Too Complex for Any of Us to Understand
Tim Maughan | OneZero
“One of the dominant themes of the last few years is that nothing makes sense. …I am here to tell you that the reason so much of the world seems incomprehensible is that it is incomprehensible. From social media to the global economy to supply chains, our lives rest precariously on systems that have become so complex, and we have yielded so much of it to technologies and autonomous actors that no one totally comprehends it all.”
The Conscience of Silicon Valley
Zach Baron | GQ
“What I really hoped to do, I said, was to talk about the future and how to live in it. This year feels like a crossroads; I do not need to explain what I mean by this. …I want to destroy my computer, through which I now work and ‘have drinks’ and stare at blurry simulations of my parents sometimes; I want to kneel down and pray to it like a god. I want someone—I want Jaron Lanier—to tell me where we’re going, and whether it’s going to be okay when we get there. Lanier just nodded. All right, then.”
Yes to Tech Optimism. And Pessimism.
Shira Ovide | The New York Times
“Technology is not something that exists in a bubble; it is a phenomenon that changes how we live or how our world works in ways that help and hurt. That calls for more humility and bridges across the optimism-pessimism divide from people who make technology, those of us who write about it, government officials and the public. We need to think on the bright side. And we need to consider the horribles.”
How Afrofuturism Can Help the World Mend
C. Brandon Ogbunu | Wired
“…[W. E. B. DuBois’] ‘The Comet’ helped lay the foundation for a paradigm known as Afrofuturism. A century later, as a comet carrying disease and social unrest has upended the world, Afrofuturism may be more relevant than ever. Its vision can help guide us out of the rubble, and help us to consider universes of better alternatives.”
Wikipedia Is the Last Best Place on the Internet
Richard Cooke | Wired
“More than an encyclopedia, Wikipedia has become a community, a library, a constitution, an experiment, a political manifesto—the closest thing there is to an online public square. It is one of the few remaining places that retains the faintly utopian glow of the early World Wide Web.”
Can Genetic Engineering Bring Back the American Chestnut?
Gabriel Popkin | The New York Times Magazine
“The geneticists’ research forces conservationists to confront, in a new and sometimes discomfiting way, the prospect that repairing the natural world does not necessarily mean returning to an unblemished Eden. It may instead mean embracing a role that we’ve already assumed: engineers of everything, including nature.”
At the Limits of Thought
David C. Krakauer | Aeon
“A schism is emerging in the scientific enterprise. On the one side is the human mind, the source of every story, theory, and explanation that our species holds dear. On the other stand the machines, whose algorithms possess astonishing predictive power but whose inner workings remain radically opaque to human observers.”
Is the Internet Conscious? If It Were, How Would We Know?
Meghan O’Gieblyn | Wired
“Does the internet behave like a creature with an internal life? Does it manifest the fruits of consciousness? There are certainly moments when it seems to. Google can anticipate what you’re going to type before you fully articulate it to yourself. Facebook ads can intuit that a woman is pregnant before she tells her family and friends. It is easy, in such moments, to conclude that you’re in the presence of another mind—though given the human tendency to anthropomorphize, we should be wary of quick conclusions.”
The Internet Is an Amnesia Machine
Simon Pitt | OneZero
“There was a time when I didn’t know what a Baby Yoda was. Then there was a time I couldn’t go online without reading about Baby Yoda. And now, Baby Yoda is a distant, shrugging memory. Soon there will be a generation of people who missed the whole thing and for whom Baby Yoda is as meaningless as it was for me a year ago.”
Digital Pregnancy Tests Are Almost as Powerful as the Original IBM PC
Tom Warren | The Verge
“Each test, which costs less than $5, includes a processor, RAM, a button cell battery, and a tiny LCD screen to display the result. …Foone speculates that this device is ‘probably faster at number crunching and basic I/O than the CPU used in the original IBM PC.’ IBM’s original PC was based on Intel’s 8088 microprocessor, an 8-bit chip that operated at 5Mhz. The difference here is that this is a pregnancy test you pee on and then throw away.”
The Party Goes on in Massive Online Worlds
Cecilia D’Anastasio | Wired
“We’re more stand-outside types than the types to cast a flashy glamour spell and chat up the nearest cat girl. But, hey, it’s Final Fantasy XIV online, and where my body sat in New York, the epicenter of America’s Covid-19 outbreak, there certainly weren’t any parties.”
The Facebook Groups Where People Pretend the Pandemic Isn’t Happening
Kaitlyn Tiffany | The Atlantic
“Losing track of a friend in a packed bar or screaming to be heard over a live band is not something that’s happening much in the real world at the moment, but it happens all the time in the 2,100-person Facebook group ‘a group where we all pretend we’re in the same venue.’ So does losing shoes and Juul pods, and shouting matches over which bands are the saddest, and therefore the greatest.”
Did You Fly a Jetpack Over Los Angeles This Weekend? Because the FBI Is Looking for You
Tom McKay | Gizmodo
“Did you fly a jetpack over Los Angeles at approximately 3,000 feet on Sunday? Some kind of tiny helicopter? Maybe a lawn chair with balloons tied to it? If the answer to any of the above questions is ‘yes,’ you should probably lay low for a while (by which I mean cool it on the single-occupant flying machine). That’s because passing airline pilots spotted you, and now it’s this whole thing with the FBI and the Federal Aviation Administration, both of which are investigating.”
Image Credit: Thomas Kinto / Unsplash Continue reading →
Posted in Human Robots
#437912 “Boston Dynamics Will Continue to ...
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
#437905 New Deep Learning Method Helps Robots ...
One of the biggest things standing in the way of the robot revolution is their inability to adapt. That may be about to change though, thanks to a new approach that blends pre-learned skills on the fly to tackle new challenges.
Put a robot in a tightly-controlled environment and it can quickly surpass human performance at complex tasks, from building cars to playing table tennis. But throw these machines a curve ball and they’re in trouble—just check out this compilation of some of the world’s most advanced robots coming unstuck in the face of notoriously challenging obstacles like sand, steps, and doorways.
The reason robots tend to be so fragile is that the algorithms that control them are often manually designed. If they encounter a situation the designer didn’t think of, which is almost inevitable in the chaotic real world, then they simply don’t have the tools to react.
Rapid advances in AI have provided a potential workaround by letting robots learn how to carry out tasks instead of relying on hand-coded instructions. A particularly promising approach is deep reinforcement learning, where the robot interacts with its environment through a process of trial-and-error and is rewarded for carrying out the correct actions. Over many repetitions it can use this feedback to learn how to accomplish the task at hand.
But the approach requires huge amounts of data to solve even simple tasks. And most of the things we would want a robot to do are actually comprised of many smaller tasks—for instance, delivering a parcel involves learning how to pick an object up, how to walk, how to navigate, and how to pass an object to someone else, among other things.
Training all these sub-tasks simultaneously is hugely complex and far beyond the capabilities of most current AI systems, so many experiments so far have focused on narrow skills. Some have tried to train AI on multiple skills separately and then use an overarching system to flip between these expert sub-systems, but these approaches still can’t adapt to completely new challenges.
Building off this research, though, scientists have now created a new AI system that can blend together expert sub-systems specialized for a specific task. In a paper in Science Robotics, they explain how this allows a four-legged robot to improvise new skills and adapt to unfamiliar challenges in real time.
The technique, dubbed multi-expert learning architecture (MELA), relies on a two-stage training approach. First the researchers used a computer simulation to train two neural networks to carry out two separate tasks: trotting and recovering from a fall.
They then used the models these two networks learned as seeds for eight other neural networks specialized for more specific motor skills, like rolling over or turning left or right. The eight “expert networks” were trained simultaneously along with a “gating network,” which learns how to combine these experts to solve challenges.
Because the gating network synthesizes the expert networks rather than switching them on sequentially, MELA is able to come up with blends of different experts that allow it to tackle problems none could solve alone.
The authors liken the approach to training people in how to play soccer. You start out by getting them to do drills on individual skills like dribbling, passing, or shooting. Once they’ve mastered those, they can then intelligently combine them to deal with more dynamic situations in a real game.
After training the algorithm in simulation, the researchers uploaded it to a four-legged robot and subjected it to a battery of tests, both indoors and outdoors. The robot was able to adapt quickly to tricky surfaces like gravel or pebbles, and could quickly recover from being repeatedly pushed over before continuing on its way.
There’s still some way to go before the approach could be adapted for real-world commercially useful robots. For a start, MELA currently isn’t able to integrate visual perception or a sense of touch; it simply relies on feedback from the robot’s joints to tell it what’s going on around it. The more tasks you ask the robot to master, the more complex and time-consuming the training will get.
Nonetheless, the new approach points towards a promising way to make multi-skilled robots become more than the sum of their parts. As much fun as it is, it seems like laughing at compilations of clumsy robots may soon be a thing of the past.
Image Credit: Yang et al., Science Robotics Continue reading →
Posted in Human Robots
#437859 We Can Do Better Than Human-Like Hands ...
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.
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Posted in Human Robots
#437857 Video Friday: Robotic Third Hand Helps ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):
ICRA 2020 – June 1-15, 2020 – [Virtual Conference]
RSS 2020 – July 12-16, 2020 – [Virtual Conference]
CLAWAR 2020 – August 24-26, 2020 – [Virtual Conference]
ICUAS 2020 – September 1-4, 2020 – Athens, Greece
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
ICSR 2020 – November 14-16, 2020 – Golden, Colorado
Let us know if you have suggestions for next week, and enjoy today’s videos.
We are seeing some exciting advances in the development of supernumerary robotic limbs. But one thing about this technology remains a major challenge: How do you control the extra limb if your own hands are busy—say, if you’re carrying a package? MIT researchers at Professor Harry Asada’s lab have an idea. They are using subtle finger movements in sensorized gloves to control the supernumerary limb. The results are promising, and they’ve demonstrated a waist-mounted arm with a qb SoftHand that can help you with doors, elevators, and even handshakes.
[ Paper ]
ROBOPANDA
Fluid actuated soft robots, or fluidic elastomer actuators, have shown great potential in robotic applications where large compliance and safe interaction are dominant concerns. They have been widely studied in wearable robotics, prosthetics, and rehabilitations in recent years. However, such soft robots and actuators are tethered to a bulky pump and controlled by various valves, limiting their applications to a small confined space. In this study, we report a new and effective approach to fluidic power actuation that is untethered, easy to design, fabricate, control, and allows various modes of actuation. In the proposed approach, a sealed elastic tube filled with fluid (gas or liquid) is segmented by adaptors. When twisting a segment, two major effects could be observed: (1) the twisted segment exhibits a contraction force and (2) other segments inflate or deform according to their constraint patterns.
[ Paper ]
And now: “Magnetic cilia carpets.”
[ ETH Zurich ]
To adhere to government recommendations while maintaining requirements for social distancing during the COVID-19 pandemic, Yaskawa Motoman is now utilizing an HC10DT collaborative robot to take individual employee temperatures. Named “Covie”, the design and fabrication of the robotic solution and its software was a combined effort by Yaskawa Motoman’s Technology Advancement Team (TAT) and Product Solutions Group (PSG), as well as a group of robotics students from the University of Dayton.
They should have programmed it to nod if your temperature was normal, and smacked you upside the head while yelling “GO HOME” if it wasn’t.
[ Yaskawa ]
Driving slowly on pre-defined routes, ZMP’s RakuRo autonomous vehicle helps people with mobility challenges enjoy cherry blossoms in Japan.
RakuRo costs about US $1,000 per month to rent, but ZMP suggests that facilities or groups of ~10 people could get together and share one, which makes the cost much more reasonable.
[ ZMP ]
Jessy Grizzle from the Dynamic Legged Locomotion Lab at the University of Michigan writes:
Our lab closed on March 20, 2020 under the State of Michigan’s “Stay Home, Stay Safe” order. For a 24-hour period, it seemed that our labs would be “sanitized” during our absence. Since we had no idea what that meant, we decided that Cassie Blue needed to “Stay Home, Stay Safe” as well. We loaded up a very expensive robot and took her off campus. On May 26, we were allowed to re-open our laboratory. After thoroughly cleaning the lab, disinfecting tools and surfaces, developing and getting approval for new safe operation procedures, we then re-organized our work areas to respect social distancing requirements and brought Cassie back to the laboratory.
During the roughly two months we were working remotely, the lab’s members got a lot done. Papers were written, dissertation proposals were composed, and plans for a new course, ROB 101, Computational Linear Algebra, were developed with colleagues. In addition, one of us (Yukai Gong) found the lockdown to his liking! He needed the long period of quiet to work through some new ideas for how to control 3D bipedal robots.
[ Michigan Robotics ]
Thanks Jesse and Bruce!
You can tell that this video of how Pepper has been useful during COVID-19 is not focused on the United States, since it refers to the pandemic in past tense.
[ Softbank Robotics ]
NASA’s water-seeking robotic Moon rover just booked a ride to the Moon’s South Pole. Astrobotic of Pittsburgh, Pennsylvania, has been selected to deliver the Volatiles Investigating Polar Exploration Rover, or VIPER, to the Moon in 2023.
[ NASA ]
This could be the most impressive robotic gripper demo I have ever seen.
[ Soft Robotics ]
Whiz, an autonomous vacuum sweeper, innovates the cleaning industry by automating tedious tasks for your team. Easy to train, easy to use, Whiz works with your staff to deliver a high-quality clean while increasing efficiency and productivity.
[ Softbank Robotics ]
About 40 seconds into this video, a robot briefly chases a goose.
[ Ghost Robotics ]
SwarmRail is a new concept for rail-guided omnidirectional mobile robot systems. It aims for a highly flexible production process in the factory of the future by opening up the available work space from above. This means that transport and manipulation tasks can be carried out by floor- and ceiling-bound robot systems. The special feature of the system is the combination of omnidirectionally mobile units with a grid-shaped rail network, which is characterized by passive crossings and a continuous gap between the running surfaces of the rails. Through this gap, a manipulator operating below the rail can be connected to a mobile unit traveling on the rail.
[ DLRRMC ]
RightHand Robotics (RHR), a leader in providing robotic piece-picking solutions, is partnered with PALTAC Corporation, Japan’s largest wholesaler of consumer packaged goods. The collaboration introduces RightHand’s newest piece-picking solution to the Japanese market, with multiple workstations installed in PALTAC’s newest facility, RDC Saitama, which opened in 2019 in Sugito, Saitama Prefecture, Japan.
[ RightHand Robotics ]
From the ICRA 2020, a debate on the “Future of Robotics Research,” addressing such issues as “robotics research is over-reliant on benchmark datasets and simulation” and “robots designed for personal or household use have failed because of fundamental misunderstandings of Human-Robot Interaction (HRI).”
[ Robotics Debates ]
MassRobotics has a series of interviews where robotics celebrities are interviewed by high school students.The students are perhaps a little awkward (remember being in high school?), but it’s honest and the questions are interesting. The first two interviews are with Laurie Leshin, who worked on space robots at NASA and is now President of Worcester Polytechnic Institute, and Colin Angle, founder and CEO of iRobot.
[ MassRobotics ]
Thanks Andrew!
In this episode of the Voices from DARPA podcast, Dr. Timothy Chung, a program manager since 2016 in the agency’s Tactical Technology Office, delves into his robotics and autonomous technology programs – the Subterranean (SubT) Challenge and OFFensive Swarm-Enabled Tactics (OFFSET). From robot soccer to live-fly experimentation programs involving dozens of unmanned aircraft systems (UASs), he explains how he aims to assist humans heading into unknown environments via advances in collaborative autonomy and robotics.
[ DARPA ] Continue reading →
Posted in Human Robots