Tag Archives: hard

#437940 How Boston Dynamics Taught Its Robots to ...

Posted on January 7, 2021 by Android

A week ago, Boston Dynamics posted a video of Atlas, Spot, and Handle dancing to “Do You Love Me.” It was, according to the video description, a way “to celebrate the start of what we hope will be a happier year.” As of today the video has been viewed nearly 24 million times, and the popularity is no surprise, considering the compelling mix of technical prowess and creativity on display.

Strictly speaking, the stuff going on in the video isn’t groundbreaking, in the sense that we’re not seeing any of the robots demonstrate fundamentally new capabilities, but that shouldn’t take away from how impressive it is—you’re seeing state-of-the-art in humanoid robotics, quadrupedal robotics, and whatever-the-heck-Handle-is robotics.

What is unique about this video from Boston Dynamics is the artistic component. We know that Atlas can do some practical tasks, and we know it can do some gymnastics and some parkour, but dancing is certainly something new. To learn more about what it took to make these dancing robots happen (and it’s much more complicated than it might seem), we spoke with Aaron Saunders, Boston Dynamics’ VP of Engineering.

Saunders started at Boston Dynamics in 2003, meaning that he’s been a fundamental part of a huge number of Boston Dynamics’ robots, even the ones you may have forgotten about. Remember LittleDog, for example? A team of two designed and built that adorable little quadruped, and Saunders was one of them.

While he’s been part of the Atlas project since the beginning (and had a hand in just about everything else that Boston Dynamics works on), Saunders has spent the last few years leading the Atlas team specifically, and he was kind enough to answer our questions about their dancing robots.

IEEE Spectrum: What’s your sense of how the Internet has been reacting to the video?

Aaron Saunders: We have different expectations for the videos that we make; this one was definitely anchored in fun for us. The response on YouTube was record-setting for us: We received hundreds of emails and calls with people expressing their enthusiasm, and also sharing their ideas for what we should do next, what about this song, what about this dance move, so that was really fun. My favorite reaction was one that I got from my 94-year-old grandma, who watched the video on YouTube and then sent a message through the family asking if I’d taught the robot those sweet moves. I think this video connected with a broader audience, because it mixed the old-school music with new technology.

We haven’t seen Atlas move like this before—can you talk about how you made it happen?

We started by working with dancers and a choreographer to create an initial concept for the dance by composing and assembling a routine. One of the challenges, and probably the core challenge for Atlas in particular, was adjusting human dance moves so that they could be performed on the robot. To do that, we used simulation to rapidly iterate through movement concepts while soliciting feedback from the choreographer to reach behaviors that Atlas had the strength and speed to execute. It was very iterative—they would literally dance out what they wanted us to do, and the engineers would look at the screen and go “that would be easy” or “that would be hard” or “that scares me.” And then we’d have a discussion, try different things in simulation, and make adjustments to find a compatible set of moves that we could execute on Atlas.

Throughout the project, the time frame for creating those new dance moves got shorter and shorter as we built tools, and as an example, eventually we were able to use that toolchain to create one of Atlas’ ballet moves in just one day, the day before we filmed, and it worked. So it’s not hand-scripted or hand-coded, it’s about having a pipeline that lets you take a diverse set of motions, that you can describe through a variety of different inputs, and push them through and onto the robot.

Image: Boston Dynamics

Were there some things that were particularly difficult to translate from human dancers to Atlas? Or, things that Atlas could do better than humans?

Some of the spinning turns in the ballet parts took more iterations to get to work, because they were the furthest from leaping and running and some of the other things that we have more experience with, so they challenged both the machine and the software in new ways. We definitely learned not to underestimate how flexible and strong dancers are—when you take elite athletes and you try to do what they do but with a robot, it’s a hard problem. It’s humbling. Fundamentally, I don’t think that Atlas has the range of motion or power that these athletes do, although we continue developing our robots towards that, because we believe that in order to broadly deploy these kinds of robots commercially, and eventually in a home, we think they need to have this level of performance.

One thing that robots are really good at is doing something over and over again the exact same way. So once we dialed in what we wanted to do, the robots could just do it again and again as we played with different camera angles.

I can understand how you could use human dancers to help you put together a routine with Atlas, but how did that work with Spot, and particularly with Handle?

I think the people we worked with actually had a lot of talent for thinking about motion, and thinking about how to express themselves through motion. And our robots do motion really well—they’re dynamic, they’re exciting, they balance. So I think what we found was that the dancers connected with the way the robots moved, and then shaped that into a story, and it didn’t matter whether there were two legs or four legs. When you don’t necessarily have a template of animal motion or human behavior, you just have to think a little harder about how to go about doing something, and that’s true for more pragmatic commercial behaviors as well.

“We used simulation to rapidly iterate through movement concepts while soliciting feedback from the choreographer to reach behaviors that Atlas had the strength and speed to execute. It was very iterative—they would literally dance out what they wanted us to do, and the engineers would look at the screen and go ‘that would be easy’ or ‘that would be hard’ or ‘that scares me.’”
—Aaron Saunders, Boston Dynamics

How does the experience that you get teaching robots to dance, or to do gymnastics or parkour, inform your approach to robotics for commercial applications?

We think that the skills inherent in dance and parkour, like agility, balance, and perception, are fundamental to a wide variety of robot applications. Maybe more importantly, finding that intersection between building a new robot capability and having fun has been Boston Dynamics’ recipe for robotics—it’s a great way to advance.

One good example is how when you push limits by asking your robots to do these dynamic motions over a period of several days, you learn a lot about the robustness of your hardware. Spot, through its productization, has become incredibly robust, and required almost no maintenance—it could just dance all day long once you taught it to. And the reason it’s so robust today is because of all those lessons we learned from previous things that may have just seemed weird and fun. You’ve got to go into uncharted territory to even know what you don’t know.

Image: Boston Dynamics

It’s often hard to tell from watching videos like these how much time it took to make things work the way you wanted them to, and how representative they are of the actual capabilities of the robots. Can you talk about that?

Let me try to answer in the context of this video, but I think the same is true for all of the videos that we post. We work hard to make something, and once it works, it works. For Atlas, most of the robot control existed from our previous work, like the work that we’ve done on parkour, which sent us down a path of using model predictive controllers that account for dynamics and balance. We used those to run on the robot a set of dance steps that we’d designed offline with the dancers and choreographer. So, a lot of time, months, we spent thinking about the dance and composing the motions and iterating in simulation.

Dancing required a lot of strength and speed, so we even upgraded some of Atlas’ hardware to give it more power. Dance might be the highest power thing we’ve done to date—even though you might think parkour looks way more explosive, the amount of motion and speed that you have in dance is incredible. That also took a lot of time over the course of months; creating the capability in the machine to go along with the capability in the algorithms.

Once we had the final sequence that you see in the video, we only filmed for two days. Much of that time was spent figuring out how to move the camera through a scene with a bunch of robots in it to capture one continuous two-minute shot, and while we ran and filmed the dance routine multiple times, we could repeat it quite reliably. There was no cutting or splicing in that opening two-minute shot.

There were definitely some failures in the hardware that required maintenance, and our robots stumbled and fell down sometimes. These behaviors are not meant to be productized and to be a 100 percent reliable, but they’re definitely repeatable. We try to be honest with showing things that we can do, not a snippet of something that we did once. I think there’s an honesty required in saying that you’ve achieved something, and that’s definitely important for us.

You mentioned that Spot is now robust enough to dance all day. How about Atlas? If you kept on replacing its batteries, could it dance all day, too?

Atlas, as a machine, is still, you know… there are only a handful of them in the world, they’re complicated, and reliability was not a main focus. We would definitely break the robot from time to time. But the robustness of the hardware, in the context of what we were trying to do, was really great. And without that robustness, we wouldn’t have been able to make the video at all. I think Atlas is a little more like a helicopter, where there’s a higher ratio between the time you spend doing maintenance and the time you spend operating. Whereas with Spot, the expectation is that it’s more like a car, where you can run it for a long time before you have to touch it.

When you’re teaching Atlas to do new things, is it using any kind of machine learning? And if not, why not?

As a company, we’ve explored a lot of things, but Atlas is not using a learning controller right now. I expect that a day will come when we will. Atlas’ current dance performance uses a mixture of what we like to call reflexive control, which is a combination of reacting to forces, online and offline trajectory optimization, and model predictive control. We leverage these techniques because they’re a reliable way of unlocking really high performance stuff, and we understand how to wield these tools really well. We haven’t found the end of the road in terms of what we can do with them.

We plan on using learning to extend and build on the foundation of software and hardware that we’ve developed, but I think that we, along with the community, are still trying to figure out where the right places to apply these tools are. I think you’ll see that as part of our natural progression.

Image: Boston Dynamics

Much of Atlas’ dynamic motion comes from its lower body at the moment, but parkour makes use of upper body strength and agility as well, and we’ve seen some recent concept images showing Atlas doing vaults and pullups. Can you tell us more?

Humans and animals do amazing things using their legs, but they do even more amazing things when they use their whole bodies. I think parkour provides a fantastic framework that allows us to progress towards whole body mobility. Walking and running was just the start of that journey. We’re progressing through more complex dynamic behaviors like jumping and spinning, that’s what we’ve been working on for the last couple of years. And the next step is to explore how using arms to push and pull on the world could extend that agility.

One of the missions that I’ve given to the Atlas team is to start working on leveraging the arms as much as we leverage the legs to enhance and extend our mobility, and I’m really excited about what we’re going to be working on over the next couple of years, because it’s going to open up a lot more opportunities for us to do exciting stuff with Atlas.

What’s your perspective on hydraulic versus electric actuators for highly dynamic robots?

Across my career at Boston Dynamics, I’ve felt passionately connected to so many different types of technology, but I’ve settled into a place where I really don’t think this is an either-or conversation anymore. I think the selection of actuator technology really depends on the size of the robot that you’re building, what you want that robot to do, where you want it to go, and many other factors. Ultimately, it’s good to have both kinds of actuators in your toolbox, and I love having access to both—and we’ve used both with great success to make really impressive dynamic machines.

I think the only delineation between hydraulic and electric actuators that appears to be distinct for me is probably in scale. It’s really challenging to make tiny hydraulic things because the industry just doesn’t do a lot of that, and the reciprocal is that the industry also doesn’t tend to make massive electrical things. So, you may find that to be a natural division between these two technologies.

Besides what you’re working on at Boston Dynamics, what recent robotics research are you most excited about?

For us as a company, we really love to follow advances in sensing, computer vision, terrain perception, these are all things where the better they get, the more we can do. For me personally, one of the things I like to follow is manipulation research, and in particular manipulation research that advances our understanding of complex, friction-based interactions like sliding and pushing, or moving compliant things like ropes.

We’re seeing a shift from just pinching things, lifting them, moving them, and dropping them, to much more meaningful interactions with the environment. Research in that type of manipulation I think is going to unlock the potential for mobile manipulators, and I think it’s really going to open up the ability for robots to interact with the world in a rich way.

Is there anything else you’d like people to take away from this video?

For me personally, and I think it’s because I spend so much of my time immersed in robotics and have a deep appreciation for what a robot is and what its capabilities and limitations are, one of my strong desires is for more people to spend more time with robots. We see a lot of opinions and ideas from people looking at our videos on YouTube, and it seems to me that if more people had opportunities to think about and learn about and spend time with robots, that new level of understanding could help them imagine new ways in which robots could be useful in our daily lives. I think the possibilities are really exciting, and I just want more people to be able to take that journey. Continue reading →

Posted in Human Robots

#437935 Start the New Year Right: By Watching ...

Posted on January 6, 2021 by Android

I don’t need to tell you that 2020 was a tough year. There was almost nothing good about it, and we saw it off with a “good riddance” and hopes for a better 2021. But robotics company Boston Dynamics took a different approach to closing out the year: when all else fails, why not dance?

The company released a video last week that I dare you to watch without laughing—or at the very least, cracking a pretty big smile. Because, well, dancing robots are funny. And it’s not just one dancing robot, it’s four of them: two humanoid Atlas bots, one four-legged Spot, and one Handle, a bot-on-wheels built for materials handling.

The robots’ killer moves look almost too smooth and coordinated to be real, leading many to speculate that the video was computer-generated. But if you can trust Elon Musk, there’s no CGI here.

This is not CGI https://t.co/VOivE97vPR

— Elon Musk (@elonmusk) December 29, 2020

Boston Dynamics went through a lot of changes in the last ten years; it was acquired by Google in 2013, then sold to Japanese conglomerate SoftBank in 2017 before being acquired again by Hyundai just a few weeks ago for $1.1 billion. But this isn’t the first time they teach a robot to dance and make a video for all the world to enjoy; Spot tore up the floor to “Uptown Funk” back in 2018.

Four-legged Spot went commercial in June, with a hefty price tag of $74,500, and was put to some innovative pandemic-related uses, including remotely measuring patients’ vital signs and reminding people to social distance.

Hyundai plans to implement its newly-acquired robotics prowess for everything from service and logistics robots to autonomous driving and smart factories.

They’ll have their work cut out for them. Besides being hilarious, kind of heartwarming, and kind of creepy all at once, the robots’ new routine is pretty impressive from an engineering standpoint. Compare it to a 2016 video of Atlas trying to pick up a box (I know it’s a machine with no feelings, but it’s hard not to feel a little bit bad for it, isn’t it?), and it’s clear Boston Dynamics’ technology has made huge strides. It wouldn’t be surprising if, in two years’ time, we see a video of a flash mob of robots whose routine includes partner dancing and back flips (which, admittedly, Atlas can already do).

In the meantime, though, this one is pretty entertaining—and not a bad note on which to start the new year.

Image Credit: Boston Dynamics 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

#437884 Hyundai Buys Boston Dynamics for Nearly ...

Posted on December 11, 2020 by Android

This morning just after 3 a.m. ET, Boston Dynamics sent out a media release confirming that Hyundai Motor Group has acquired a controlling interest in the company that values Boston Dynamics at US $1.1 billion:

Under the agreement, Hyundai Motor Group will hold an approximately 80 percent stake in Boston Dynamics and SoftBank, through one of its affiliates, will retain an approximately 20 percent stake in Boston Dynamics after the closing of the transaction.

The release is very long, but does have some interesting bits—we’ll go through them, and talk about what this might mean for both Boston Dynamics and Hyundai.

We’ve asked Boston Dynamics for comment, but they’ve been unusually quiet for the last few days (I wonder why!). So at this point just keep in mind that the only things we know for sure are the ones in the release. If (when?) we hear anything from either Boston Dynamics or Hyundai, we’ll update this post.

The first thing to be clear on is that the acquisition is split between Hyundai Motor Group’s affiliates, including Hyundai Motor, Hyundai Mobis, and Hyundai Glovis. Hyundai Motor makes cars, Hyundai Mobis makes car parts and seems to be doing some autonomous stuff as well, and Hyundai Glovis does logistics. There are many other groups that share the Hyundai name, but they’re separate entities, at least on paper. For example, there’s a Hyundai Robotics, but that’s part of Hyundai Heavy Industries, a different company than Hyundai Motor Group. But for this article, when we say “Hyundai,” we’re talking about Hyundai Motor Group.

What’s in it for Hyundai?
Let’s get into the press release, which is filled with press release-y terms like “synergies” and “working together”—you can view the whole thing here—but still has some parts that convey useful info.

By establishing a leading presence in the field of robotics, the acquisition will mark another major step for Hyundai Motor Group toward its strategic transformation into a Smart Mobility Solution Provider. To propel this transformation, Hyundai Motor Group has invested substantially in development of future technologies, including in fields such as autonomous driving technology, connectivity, eco-friendly vehicles, smart factories, advanced materials, artificial intelligence (AI), and robots.

If Hyundai wants to be a “Smart Mobility Solution Provider” with a focus on vehicles, it really seems like there’s a whole bunch of other ways they could have spent most of a billion dollars that would get them there quicker. Will Boston Dynamics’ expertise help them develop autonomous driving technology? Sure, I guess, but why not just buy an autonomous car startup instead? Boston Dynamics is more about “robots,” which happens to be dead last on the list above.

There was some speculation a couple of weeks ago that Hyundai was going to try and leverage Boston Dynamics to make a real version of this hybrid wheeled/legged concept car, so if that’s what Hyundai means by “Smart Mobility Solution Provider,” then I suppose the Boston Dynamics acquisition makes more sense. Still, I think that’s unlikely, because it’s just a concept car, after all.

In addition to “smart mobility,” which seems like a longer-term goal for Hyundai, the company also mentions other, more immediate benefits from the acquisition:

Advanced robotics offer opportunities for rapid growth with the potential to positively impact society in multiple ways. Boston Dynamics is the established leader in developing agile, mobile robots that have been successfully integrated into various business operations. The deal is also expected to allow Hyundai Motor Group and Boston Dynamics to leverage each other’s respective strengths in manufacturing, logistics, construction and automation.

“Successfully integrated” might be a little optimistic here. They’re talking about Spot, of course, but I think the best you could say at this point is that Spot is in the middle of some promising pilot projects. Whether it’ll be successfully integrated in the sense that it’ll have long-term commercial usefulness and value remains to be seen. I’m optimistic about this as well, but Spot is definitely not there yet.

What does probably hold a lot of value for Hyundai is getting Spot, Pick, and perhaps even Handle into that “manufacturing, logistics, construction” stuff. This is the bread and butter for robots right now, and Boston Dynamics has plenty of valuable technology to offer in those spaces.

Photo: Bob O’Connor

Boston Dynamics is selling Spot for $74,500, shipping included.

Betting on Spot and Pick
With Boston Dynamics founder Marc Raibert’s transition to Chairman of the company, the CEO position is now occupied by Robert Playter, the long-time VP of engineering and more recently COO at Boston Dynamics. Here’s his statement from the release:

“Boston Dynamics’ commercial business has grown rapidly as we’ve brought to market the first robot that can automate repetitive and dangerous tasks in workplaces designed for human-level mobility. We and Hyundai share a view of the transformational power of mobility and look forward to working together to accelerate our plans to enable the world with cutting edge automation, and to continue to solve the world’s hardest robotics challenges for our customers.”

Whether Spot is in fact “the first robot that can automate repetitive and dangerous tasks in workplaces designed for human-level mobility” on the market is perhaps something that could be argued against, although I won’t. Whether or not it was the first robot that can do these kinds of things, it’s definitely not the only robot that do these kinds of things, and going forward, it’s going to be increasingly challenging for Spot to maintain its uniqueness.

For a long time, Boston Dynamics totally owned the quadruped space. Now, they’re one company among many—ANYbotics and Unitree are just two examples of other quadrupeds that are being successfully commercialized. Spot is certainly very capable and easy to use, and we shouldn’t underestimate the effort required to create a robot as complex as Spot that can be commercially used and supported. But it’s not clear how long they’ll maintain that advantage, with much more affordable platforms coming out of Asia, and other companies offering some unique new capabilities.

Photo: Boston Dynamics

Boston Dynamics’ Handle is an all-electric robot featuring a leg-wheel hybrid mobility system, a manipulator arm with a vacuum gripper, and a counterbalancing tail.

Boston Dynamics’ picking system, which stemmed from their 2019 acquisition of Kinema Systems, faces the same kinds of challenges—it’s very good, but it’s not totally unique.

Boston Dynamics produces highly capable mobile robots with advanced mobility, dexterity and intelligence, enabling automation in difficult, dangerous, or unstructured environments. The company launched sales of its first commercial robot, Spot in June of 2020 and has since sold hundreds of robots in a variety of industries, such as power utilities, construction, manufacturing, oil and gas, and mining. Boston Dynamics plans to expand the Spot product line early next year with an enterprise version of the robot with greater levels of autonomy and remote inspection capabilities, and the release of a robotic arm, which will be a breakthrough in mobile manipulation.

Boston Dynamics is also entering the logistics automation market with the industry leading Pick, a computer vision-based depalletizing solution, and will introduce a mobile robot for warehouses in 2021.

Huh. We’ll be trying to figure out what “greater levels of autonomy” means, as well as whether the “mobile robot for warehouses” is Handle, or something more like an autonomous mobile robot (AMR) platform. I’d honestly be surprised if Handle was ready for work outside of Boston Dynamics next year, and it’s hard to imagine how Boston Dynamics could leverage their expertise into the AMR space with something that wouldn’t just seem… Dull, compared to what they usually do. I hope to be surprised, though!

A new deep-pocketed benefactor

Hyundai Motor Group’s decision to acquire Boston Dynamics is based on its growth potential and wide range of capabilities.

“Wide range of capabilities” we get, but that other phrase, “growth potential,” has a heck of a lot wrapped up in it. At the moment, Boston Dynamics is nowhere near profitable, as far as we know. SoftBank acquired Boston Dynamics in 2017 for between one hundred and two hundred million, and over the last three years they’ve poured hundreds of millions more into Boston Dynamics.

Hyundai’s 80 percent stake just means that they’ll need to take over the majority of that support, and perhaps even increase it if Boston Dynamics’ growth is one of their primary goals. Hyundai can’t have a reasonable expectation that Boston Dynamics will be profitable any time soon; they’re selling Spots now, but it’s an open question whether Spot will manage to find a scalable niche in which it’ll be useful in the sort of volume that will make it a sustainable commercial success. And even if it does become a success, it seems unlikely that Spot by itself will make a significant dent in Boston Dynamics’ burn rate anytime soon. Boston Dynamics will have more products of course, but it’s going to take a while, and Hyundai will need to support them in the interim.

Depending on whether Hyundai views Boston Dynamics as a company that does research or a company that makes robots that are useful and profitable, it may be difficult for Boston Dynamics to justify the cost to develop the
next Atlas, when the
current one still seems so far from commercialization

It’s become clear that to sustain itself, Boston Dynamics needs a benefactor with very deep pockets and a long time horizon. Initially, Boston Dynamics’ business model (or whatever you want to call it) was to do bespoke projects for defense-ish folks like DARPA, but from what we understand Boston Dynamics stopped that sort of work after Google acquired them back in 2013. From one perspective, that government funding did exactly what it was supposed to do, which was to fund the development of legged robots through low TRLs (technology readiness levels) to the point where they could start to explore commercialization.

The question now, though, is whether Hyundai is willing to let Boston Dynamics undertake the kinds of low-TRL, high-risk projects that led from BigDog to LS3 to Spot, and from PETMAN to DRC Atlas to the current Atlas. So will Hyundai be cool about the whole thing and be the sort of benefactor that’s willing to give Boston Dynamics the resources that they need to keep doing what they’re doing, without having to answer too many awkward questions about things like practicality and profitability? Hyundai can certainly afford to do this, but so could SoftBank, and Google—the question is whether Hyundai will want to, over the length of time that’s required for the development of the kind of ultra-sophisticated robotics hardware that Boston Dynamics specializes in.

To put it another way: Depending whether Hyundai’s perspective on Boston Dynamics is as a company that does research or a company that makes robots that are useful and profitable, it may be difficult for Boston Dynamics to justify the cost to develop the next Atlas, when the current one still seems so far from commercialization.

Google, SoftBank, now Hyundai

Boston Dynamics possesses multiple key technologies for high-performance robots equipped with perception, navigation, and intelligence.

Hyundai Motor Group’s AI and Human Robot Interaction (HRI) expertise is highly synergistic with Boston Dynamics’s 3D vision, manipulation, and bipedal/quadruped expertise.

As it turns out, Hyundai Motors does have its own robotics lab, called Hyundai Motors Robotics Lab. Their website is not all that great, but here’s a video from last year:

I’m not entirely clear on what Hyundai means when they use the word “synergistic” when they talk about their robotics lab and Boston Dynamics, but it’s a little bit concerning. Usually, when a big company buys a little company that specializes in something that the big company is interested in, the idea is that the little company, to some extent, will be absorbed into the big company to give them some expertise in that area. Historically, however, Boston Dynamics has been highly resistant to this, maintaining its post-acquisition independence and appearing to be very reluctant to do anything besides what it wants to do, at whatever pace it wants to do it, and as by itself as possible.

From what we understand, Boston Dynamics didn’t integrate particularly well with Google’s robotics push in 2013, and we haven’t seen much evidence that SoftBank’s experience was much different. The most direct benefit to SoftBank (or at least the most visible one) was the addition of a fleet of Spot robots to the SoftBank Hawks baseball team cheerleading squad, along with a single (that we know about) choreographed gymnastics routine from an Atlas robot that was only shown on video.

And honestly, if you were a big manufacturing company with a bunch of money and you wanted to build up your own robotics program quickly, you’d probably have much better luck picking up some smaller robotics companies who were a bit less individualistic and would probably be more amenable to integration and would cost way less than a billion dollars-ish. And if integration is ultimately Hyundai’s goal, we’ll be very sad, because it’ll likely signal the end of Boston Dynamics doing the unfettered crazy stuff that we’ve grown to love.

Photo: Bob O’Connor

Possibly the most agile humanoid robot ever built, Atlas can run, climb, jump over obstacles, and even get up after a fall.

Boston Dynamics contemplates its future

The release ends by saying that the transaction is “subject to regulatory approvals and other customary closing conditions” and “is expected to close by June of 2021.” Again, you can read the whole thing here.

My initial reaction is that, despite the “synergies” described by Hyundai, it’s certainly not immediately obvious why the company wants to own 80 percent of Boston Dynamics. I’d also like a better understanding of how they arrived at the $1.1 billion valuation. I’m not saying this because I don’t believe in what Boston Dynamics is doing or in the inherent value of the company, because I absolutely do, albeit perhaps in a slightly less tangible sense. But when you start tossing around numbers like these, a big pile of expectations inevitably comes along with them. I hope that Boston Dynamics is unique enough that the kinds of rules that normally apply to robotics companies (or companies in general) can be set aside, at least somewhat, but I also worry that what made Boston Dynamics great was the explicit funding for the kinds of radical ideas that eventually resulted in robots like Atlas and Spot.

Can Hyundai continue giving Boston Dynamics the support and freedom that they need to keep doing the kinds of things that have made them legendary? I certainly hope so. 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