Tag Archives: ATLAS

#439055 Stretch Is Boston Dynamics’ Take on a ...

Today, Boston Dynamics is announcing Stretch, a mobile robot designed to autonomously move boxes around warehouses. At first glance, you might be wondering why the heck this is a Boston Dynamics robot at all, since the dynamic mobility that we associate with most of their platforms is notably absent. The combination of strength and speed in Stretch’s arm is something we haven’t seen before in a mobile robot, and it’s what makes this a unique and potentially exciting entry into the warehouse robotics space.

Useful mobile manipulation in any environment that’s not almost entirely structured is still a significant challenge in robotics, and it requires a very difficult combination of sensing, intelligence, and dynamic motion, all of which are classic Boston Dynamics. But also classic Boston Dynamics is building really cool platforms, and only later trying to figure out a way of making them commercially viable. So why Stretch, why boxes, why now, and (the real question) why not Handle? We talk with Boston Dynamics’ Vice President of Product Engineering Kevin Blankespoor to find out.

Stretch is very explicitly a box-handling mobile robot for relatively well structured warehouses. It’s in no way designed to be a generalist that many of Boston Dynamics’ other robots are. And to be fair, this is absolutely how to make a robot that’s practical and cost effective right out of the crate: Identify a task that is dull or dirty or dangerous for humans, design a robot to do that task safely and efficiently, and deploy it with the expectation that it’ll be really good at that task but not necessarily much else. This is a very different approach than a robot like Spot, where the platform came first and the practical applications came later—with Stretch, it’s all about that specific task in a specific environment.

There are already robotic solutions for truck unloading, palletizing, and depalletizing, but Stretch seems to be uniquely capable. For truck unloading, the highest performance systems that I’m aware of are monstrous things (here’s one example from Honeywell) that use a ton of custom hardware to just sort of ingest the cargo within a trailer all at once. In a highly structured and predictable warehouse, this sort of thing may pay off over the long term, but it’s going to be extremely expensive and not very versatile at all.

Palletizing and depalletizing robots are much more common in warehouses today. They’re almost always large industrial arms surrounded by a network of custom conveyor belts and whatnot, suffering from the same sorts of constraints as a truck unloader— very capable in some situations, but generally high cost and low flexibility.

Photo: Boston Dynamics

Stretch is probably not going to be able to compete with either of these types of dedicated systems when it comes to sheer speed, but it offers lots of other critical advantages: It’s fast and easy to deploy, easy to use, and adaptable to a variety of different tasks without costly infrastructure changes. It’s also very much not Handle, which was Boston Dynamics’ earlier (although not that much earlier) attempt at a box-handling robot for warehouses, and (let’s be honest here) a much more Boston Dynamics-y thing than Stretch seems to be. To learn more about why the answer is Stretch rather than Handle, and how Stretch will fit into the warehouse of the very near future, we spoke with Kevin Blankespoor, Boston Dynamics’ VP of Product Engineering and chief engineer for both Handle and Stretch.

IEEE Spectrum: Tell me about Stretch!

Kevin Blankespoor: Stretch is the first mobile robot that we’ve designed specifically for the warehouse. It’s all about moving boxes. Stretch is a flexible robot that can move throughout the warehouse and do different tasks. During a typical day in the life of Stretch in the future, it might spend the morning on the inbound side of the warehouse unloading boxes from trucks. It might spend the afternoon in the aisles of the warehouse building up pallets to go to retailers and e-commerce facilities, and it might spend the evening on the outbound side of the warehouse loading boxes into the trucks. So, it really goes to where the work is.

There are already other robots that include truck unloading robots, palletizing and depalletizing robots, and mobile bases with arms on them. What makes Boston Dynamics the right company to introduce a new robot in this space?

We definitely thought through this, because there are already autonomous mobile robots [AMRs] out there. Most of them, though, are more like pallet movers or tote movers—they don't have an arm, and most of them are really just about moving something from point A to point B without manipulation capability. We've seen some experiments where people put arms on AMRs, but nothing that's made it very far in the market. And so when we started looking at Stretch, we realized we really needed to make a custom robot, and that it was something we could do quickly.

“We got a lot of interest from people who wanted to put Atlas to work in the warehouse, but we knew that we could build a simpler robot to do some of those same tasks.”

Stretch is built with pieces from Spot and Atlas and that gave us a big head start. For example, if you look at Stretch’s vision system, it's 2D cameras, depth sensors, and software that allows it to do obstacle detection, box detection, and localization. Those are all the same sensors and software that we've been using for years on our legged robots. And if you look closely at Stretch’s wrist joints, they're actually the same as Spot’s hips. They use the same electric motors, the same gearboxes, the same sensors, and they even have the same closed-loop controller controlling the joints.

If you were to buy an existing industrial robot arm with this kind of performance, it would be about four times heavier than the arm we built, and it's really hard to make that into a mobile robot. A lot of this came from our leg technology because it’s so important for our leg designs to be lightweight for the robots to balance. We took that same strength to weight advantage that we have, and built it into this arm. We're able to rapidly piece together things from our other robots to get us out of the gate quickly, so even though this looks like a totally different robot, we think we have a good head start going into this market.

At what point did you decide to go with an arm on a statically stable base on Stretch, rather than something more, you know, dynamic-y?

Stretch looks really different than the robots that Boston Dynamics has done in the past. But you'd be surprised how much similarity there is between our legged robots and Stretch under the hood. Looking back, we actually got our start on moving boxes with Atlas, and at that point it was just research and development. We were really trying to do force control for box grasping. We were picking up heavy boxes and maintaining balance and working on those fundamentals. We released a video of that as our first next-gen Atlas video, and it was interesting. We got a lot of interest from people who wanted to put Atlas to work in the warehouse, but we knew that we could build a simpler robot to do some of those same tasks.

So at this point we actually came up with Handle. The intent of Handle was to do a couple things—one was, we thought we could build a simpler robot that had Atlas’ attributes. Handle has a small footprint so it can fit in tight spaces, but it can pick up heavy boxes. And in addition to that, we had always really wanted to combine wheels and legs. We’d been talking about doing that for a decade and so Handle was a chance for us to try it.

We built a couple versions of Handle, and the first one was really just a prototype to kind of explore the morphology. But the second one was more purpose-built for warehouse tasks, and we started building pallets with that one and it looked pretty good. And then we started doing truck unloading with Handle, which was the pivotal moment. Handle could do it, but it took too long. Every time Handle grasped a box, it would have to roll back and then get to a place where it could spin itself to face forward and place the box, and trucks are very tight for a robot this size, so there's not a lot of room to maneuver. We knew the whole time that there was a robot like Stretch that was another alternative, but that's really when it became clear that Stretch would have a lot of advantages, and we started working on it about a year ago.

Stretch is certainly impressive in a practical way, but I’ll admit to really hoping that something like Handle could have turned out to be a viable warehouse robot.

I love the Handle project as well, and I’m very passionate about that robot. And there was a stage before we built Stretch where we thought, “this would be pretty standard looking compared to Handle, is it going to capture enough of the Boston Dynamics secret sauce?” But when you actually dissect all the problems within Stretch that you have to tackle, there are a lot of cool robotics problems left in there—the vision system, the planning, the manipulation, the grasping of the boxes—it's a lot harder to solve than it looks, and we're excited that we're actually getting fairly far down that road now.

What happens to Handle now?

Stretch has really taken over our team as far as warehouse products go. Handle we still use occasionally as a research robot, but it’s not actively under development. Stretch is really Handle’s descendent. Handle’s not retired, exactly, but we’re just using it for things like the dance video.

There’s still potential to do cool stuff with Handle. I do think that combining wheels with legs is very cool, and largely unexplored compared to its potential. So I still think that you're gonna see versions of robots combining wheels and legs like Handle, and maybe a version of Handle in the future that does more of that. But because we're switching this thread from research into product, Stretch is really the main focus now.

How autonomous is Stretch?

Stretch is semi-autonomous, and that means it really needs to work with people to tap into its full potential. With truck unloading, for example, a person will drive Stretch into the back of the truck and then basically point Stretch in the right direction and say go. And from that point on, everything’s autonomous. Stretch has its vision system and its mobility and it can detect all the boxes, grasp all boxes, and move them onto a conveyor all autonomously. This is something that takes people hours to do manually, and Stretch can go all the way until it gets to the last box, and the truck is empty. There are some parts of the truck unloading task that do require people, like verifying that the truck is in the right place and opening the doors. But this takes a person just a few minutes, and then the robot can spend hours or as long as it takes to do its job autonomously.

There are also other tasks in the warehouse where the autonomy will increase in the future. After truck unloading, the second thing we’ll take on is order building, which will be more in the aisles of a warehouse. For that, Stretch will be navigating around the warehouse, finding the right pallet it needs to take a box from, and loading it onto a new pallet. This will be a different model with more autonomy; you’ll still have people involved to some degree, but the robot will have a higher percentage of the time where it can work independently.

What kinds of constraints is Stretch operating under? Do the boxes all have to be stacked neatly in the back of the truck, do they have to be the same size, the same color, etc?

“This will be a different model with more autonomy. You’ll still have people involved to some degree, but the robot will have a higher percentage of the time where it can work independently.”

If you think about manufacturing, where there's been automation for decades, you can go into a modern manufacturing facility and there are robot arms and conveyors and other machines. But if you look at the actual warehouse space, 90+ percent is manually operated, and that's because of what you just asked about— things that are less structured, where there’s more variety, and it's more challenging for a robot. But this is starting to change. This is really, really early days, and you’re going to be seeing a lot more robots in the warehouse space.

The warehouse robotics industry is going to grow a lot over the next decade, and a lot of that boils down to vision—the ability for robots to navigate and to understand what they’re seeing. Actually seeing boxes in real world scenarios is challenging, especially when there's a lot of variety. We've been testing our machine learning-based box detection system on Pick for a few years now, and it's gotten far enough that we know it’s one of the technical hurdles you need to overcome to succeed in the warehouse.

Can you compare the performance of Stretch to the performance of a human in a box-unloading task?

Stretch can move cases up to 50 pounds which is the OSHA limit for how much a single person's allowed to move. The peak case rate for Stretch is 800 cases per hour. You really need to keep up with the flow of goods throughout the warehouse, and 800 cases per hour should be enough for most applications. This is similar to a really good human; most humans are probably slower, and it’s hard for a human to sustain that rate, and one of the big issues with people doing this jobs is injury rates. Imagine moving really heavy boxes all day, and having to reach up high or bend down to get them—injuries are really common in this area. Truck unloading is one of the hardest jobs in a warehouse, and that’s one of the reasons we’re starting there with Stretch.

Is Stretch safe for humans to be around?

We looked at using collaborative robot arms for Stretch, but they don’t have the combination of strength and speed and reach to do this task. That’s partially just due to the laws of physics—if you want to move a 50lb box really fast, that’s a lot of energy there. So, Stretch does need to maintain separation from humans, but it’s pretty safe when it’s operating in the back of a truck.

In the middle of a warehouse, Stretch will have a couple different modes. When it's traveling around it'll be kind of like an AMR, and use a safety-rated lidar making sure that it slows down or stops as people get closer. If it's parked and the arm is moving, it'll do the same thing, monitoring anyone getting close and either slow down or stop.

How do you see Stretch interacting with other warehouse robots?

For building pallet orders, we can do that in a couple of different ways, and we’re experimenting with partners in the AMR space. So you might have an AMR that moves the pallet around and then rendezvous with Stretch, and Stretch does the manipulation part and moves boxes onto the pallet, and then the AMR scuttles off to the next rendezvous point where maybe a different Stretch meets it. We’re developing prototypes of that behavior now with a few partners. Another way to do it is Stretch can actually pull the pallet around itself and do both tasks. There are two fundamental things that happen in the warehouse: there's movement of goods, and there's manipulation of goods, and Stretch can do both.

You’re aware that Hello Robot has a mobile manipulator called Stretch, right?

Great minds think alike! We know Aaron [Edsinger] from the Google days; we all used to be in the same company, and he’s a great guy. We’re in very different applications and spaces, though— Aaron’s robot is going into research and maybe a little bit into the consumer space, while this robot is on a much bigger scale aimed at industrial applications, so I think there’s actually a lot of space between our robots, in terms of how they’ll be used.

Editor’s Note: We did check in with Aaron Edsinger at Hello Robot, and he sees things a little bit differently. “We're disappointed they chose our name for their robot,” Edsinger told us. “We're seriously concerned about it and considering our options.” We sincerely hope that Boston Dynamics and Hello Robot can come to an amicable solution on this.
What’s the timeline for commercial deployment of Stretch?

This is a prototype of the Stretch robot, and anytime we design a new robot, we always like to build a prototype as quickly as possible so we can figure out what works and what doesn't work. We did that with our bipeds and quadrupeds as well. So, we get an early look at what we need to iterate, because any time you build the first thing, it's not the right thing, and you always need to make changes to get to the final version. We've got about six of those Stretch prototypes operating now. In parallel, our hardware team is finishing up the design of the productized version of Stretch. That version of Stretch looks a lot like the prototype, but every component has been redesigned from the ground up to be manufacturable, to be reliable, and to be higher performance.

For the productized version of Stretch, we’ll build up the first units this summer, and then it’ll go on sale next year. So this is kind of a sneak peak into what the final product will be.

How much does it cost, and will you be selling Stretch, or offering it as a service?

We’re not quite ready to talk about cost yet, but it’ll be cost effective, and similar in cost to existing systems if you were to combine an industrial robot arm, custom gripper, and mobile base. We’re considering both selling and leasing as a service, but we’re not quite ready to narrow it down yet.

Photo: Boston Dynamics

As with all mobile manipulators, what Stretch can do long-term is constrained far more by software than by hardware. With a fast and powerful arm, a mobile base, a solid perception system, and 16 hours of battery life, you can imagine how different grippers could enable all kinds of different capabilities. But we’re getting ahead of ourselves, because it’s a long, long way from getting a prototype to work pretty well to getting robots into warehouses in a way that’s commercially viable long-term, even when the use case is as clear as it seems to be for Stretch.

Stretch also could signal a significant shift in focus for Boston Dynamics. While Blankespoor’s comments about Stretch leveraging Boston Dynamics’ expertise with robots like Spot and Atlas are well taken, Stretch is arguably the most traditional robot that the company has designed, and they’ve done so specifically to be able to sell robots into industry. This is what you do if you’re a robotics company who wants to make money by selling robots commercially, which (historically) has not been what Boston Dynamics is all about. Despite its bonkers valuation, Boston Dynamics ultimately needs to make money, and robots like Stretch are a good way to do it. With that in mind, I wouldn’t be surprised to see more robots like this from Boston Dynamics—robots that leverage the company’s unique technology, but that are designed to do commercially useful tasks in a somewhat less flashy way. And if this strategy keeps Boston Dynamics around (while funding some occasional creative craziness), then I’m all for it. Continue reading

Posted in Human Robots

#436950 Atlas is a gymnast

This is Atlas, the agile humanoid robot from Boston Dynamics, demonstrating its amazing gymnastic abilities!

Posted in Human Robots

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

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 ...

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

#437918 Video Friday: These Robots Wish You ...

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!):

ICCR 2020 – December 26-29, 2020 – [Online]
HRI 2021 – March 8-11, 2021 – [Online]
RoboSoft 2021 – April 12-16, 2021 – [Online]
Let us know if you have suggestions for next week, and enjoy today's videos.

Look who’s baaaack: Jibo! After being sold (twice?), this pioneering social home robot (it was first announced back in 2014!) now belongs to NTT Disruption, which was described to us as the “disruptive company of NTT Group.” We are all for disruption, so this looks like a great new home for Jibo.

[ NTT Disruption ]

Thanks Ana!

FZI's Christmas Party was a bit of a challenge this year; good thing robots are totally competent to have a part on their own.

[ FZI ]

Thanks Arne!

Do you have a lonely dog that just wants a friend to watch cat videos on YouTube with? The Danish Technological Institute has a gift idea for you.

[ DTI ]

Thanks Samuel!

Once upon a time, not so far away, there was an elf who received a very special gift. Watch this heartwarming story. Happy Holidays from the Robotiq family to yours!

Of course, these elves are not now unemployed, they've instead moved over to toy design full time!

[ Robotiq ]

An elegant Christmas video from the Dynamics System Lab, make sure and watch through the very end for a little extra cheer.

[ Dynamic Systems Lab ]

Thanks Angela!

Usually I complain when robotics companies make holiday videos without any real robots in them, but this is pretty darn cute from Yaskawa this year.

[ Yaskawa ]

Here's our little christmas gift to the fans of strange dynamic behavior. The gyro will follow any given shape as soon as the tip touches its edge and the rotation is fast enough. The friction between tip and shape generates a tangential force, creating a moment such that the gyroscopic reaction pushes the tip towards the shape. The resulting normal force produces a moment that guides the tip along the shape's edge.

[ TUM ]

Happy Holidays from Fanuc!

Okay but why does there have to be an assembly line elf just to put in those little cranks?

[ Fanuc ]

Astrobotic's cute little CubeRover is at NASA busy not getting stuck in places.

[ Astrobotic ]

Team CoSTAR is sharing more of their work on subterranean robotic exploration.

[ CoSTAR ]

Skydio Autonomy Enterprise Foundation (AEF), a new software product that delivers advanced AI-powered capabilities to assist the pilot during tactical situational awareness scenarios and detailed industrial asset inspections. Designed for professionals, it offers an enterprise-caliber flight experience through the new Skydio Enterprise application.

[ Skydio ]

GITAI's S1 autonomous robot will conduct two experiments: IVA (Intra-Vehicular Activity) tasks such as switch and cable operations, and assembly of structures and panels to demonstrate its capability for ISA (In-Space Assembly) tasks. This video was recorded in the Nanoracks Bishop Airlock mock-up facility @GITAI Tokyo office.

[ GITAI ]

It's no Atlas, but this is some impressive dynamic balancing from iCub.

[ IIT ]

The Campaign to Stop Killer Robots and I don't agree on a lot of things, and I don't agree with a lot of the assumptions made in this video, either. But, here you go!

[ CSKR ]

I don't know much about this robot, but I love it.

[ Columbia ]

Most cable-suspended robots have a very well defined workspace, but you can increase that workspace by swinging them around. Wheee!

[ Laval ]

How you know your robot's got some skill: “to evaluate the performance in climbing over the step, we compared the R.L. result to the results of 12 students who attempted to find the best planning. The RL outperformed all the group, in terms of effort and time, both in continuous (joystick) and partition planning.”

[ Zarrouk Lab ]

In the Spring 2021 semester, mechanical engineering students taking MIT class 2.007, Design and Manufacturing I, will be able to participate in the class’ iconic final robot competition from the comfort of their own home. Whether they take the class virtually or semi-virtually, students will be sent a massive kit of tools and materials to build their own unique robot along with a “Home Alone” inspired game board for the final global competition.

[ MIT ]

Well, this thing is still around!

[ Moley Robotics ]

Manuel Ahumada wrote in to share this robotic Baby Yoda that he put together with a little bit of help from Intel's OpenBot software.

[ YouTube ]

Thanks Manuel!

Here's what Zoox has been working on for the past half-decade.

[ Zoox ] Continue reading

Posted in Human Robots