Tag Archives: controlling
#439089 Ingenuity’s Chief Pilot Explains How ...
On April 11, the Mars helicopter Ingenuity will take to the skies of Mars for the first time. It will do so fully autonomously, out of necessity—the time delay between Ingenuity’s pilots at the Jet Propulsion Laboratory and Jezero Crater on Mars makes manual or even supervisory control impossible. So the best that the folks at JPL can do is practice as much as they can in simulation, and then hope that the helicopter can handle everything on its own.
Here on Earth, simulation is a critical tool for many robotics applications, because it doesn’t rely on access to expensive hardware, is non-destructive, and can be run in parallel and at faster-than-real-time speeds to focus on solving specific problems. Once you think you’ve gotten everything figured out in simulation, you can always give it a try on the real robot and see how close you came. If it works in real life, great! And if not, well, you can tweak some stuff in the simulation and try again.
For the Mars helicopter, simulation is much more important, and much higher stakes. Testing the Mars helicopter under conditions matching what it’ll find on Mars is not physically possible on Earth. JPL has flown engineering models in Martian atmospheric conditions, and they’ve used an actuated tether to mimic Mars gravity, but there’s just no way to know what it’ll be like flying on Mars until they’ve actually flown on Mars. With that in mind, the Ingenuity team has been relying heavily on simulation, since that’s one of the best tools they have to prepare for their Martian flights. We talk with Ingenuity’s Chief Pilot, Håvard Grip, to learn how it all works.
Ingenuity Facts:
Body Size: a box of tissues
Brains: Qualcomm Snapdragon 801
Weight: 1.8 kilograms
Propulsion: Two 1.2m carbon fiber rotors
Navigation sensors: VGA camera, laser altimeter, inclinometer
Ingenuity is scheduled to make its first flight no earlier than April 11. Before liftoff, the Ingenuity team will conduct a variety of pre-flight checks, including verifying the responsiveness of the control system and spinning the blades up to full speed (2,537 rpm) without lifting off. If everything looks good, the first flight will consist of a 1 meter per second climb to 3 meters, 30 seconds of hover at 3 meters while rotating in place a bit, and then a descent to landing. If Ingenuity pulls this off, that will have made its entire mission a success. There will be more flights over the next few weeks, but all it takes is one to prove that autonomous helicopter flight on Mars is possible.
Last month, we spoke with Mars Helicopter Operations Lead Tim Canham about Ingenuity’s hardware, software, and autonomy, but we wanted to know more about how the Ingenuity team has been using simulation for everything from vehicle design to flight planning. To answer our questions, we talked with JPL’s Håvard Grip, who led the development of Ingenuity’s navigation and flight control systems. Grip also has the title of Ingenuity Chief Pilot, which is pretty awesome. He summarizes this role as “operating the flight control system to make the helicopter do what we want it to do.”
IEEE Spectrum: Can you tell me about the simulation environment that JPL uses for Ingenuity’s flight planning?
Håvard Grip: We developed a Mars helicopter simulation ourselves at JPL, based on a multi-body simulation framework that’s also developed at JPL, called DARTS/DSHELL. That's a system that has been in development at JPL for about 30 years now, and it's been used in a number of missions. And so we took that multibody simulation framework, and based on it we built our own Mars helicopter simulation, put together our own rotor model, our own aerodynamics models, and everything else that's needed in order to simulate a helicopter. We also had a lot of help from the rotorcraft experts at NASA Ames and NASA Langley.
Image: NASA/JPL
Ingenuity in JPL’s flight simulator.
Without being able to test on Mars, how much validation are you able to do of what you’re seeing in simulation?
We can do a fair amount, but it requires a lot of planning. When we made our first real prototype (with a full-size rotor that looked like what we were thinking of putting on Mars) we first spent a lot of time designing it and using simulation tools to guide that design, and when we were sufficiently confident that we were close enough, and that we understood enough about it, then we actually built the thing and designed a whole suite of tests in a vacuum chamber where where we could replicate Mars atmospheric conditions. And those tests were before we tried to fly the helicopter—they were specifically targeted at what we call system identification, which has to do with figuring out what the true properties, the true dynamics of a system are, compared to what we assumed in our models. So then we got to see how well our models did, and in the places where they needed adjustment, we could go back and do that.
The simulation work that we really started after that very first initial lift test, that’s what allowed us to unlock all of the secrets to building a helicopter that can fly on Mars.
—Håvard Grip, Ingenuity Chief Pilot
We did a lot of this kind of testing. It was a big campaign, in several stages. But there are of course things that you can't fully replicate, and you do depend on simulation to tie things together. For example, we can't truly replicate Martian gravity on Earth. We can replicate the atmosphere, but not the gravity, and so we have to do various things when we fly—either make the helicopter very light, or we have to help it a little bit by pulling up on it with a string to offload some of the weight. These things don't fully replicate what it will be like on Mars. We also can't simultaneously replicate the Mars aerodynamic environment and the physical and visual surroundings that the helicopter will be flying in. These are places where simulation tools definitely come in handy, with the ability to do full flight tests from A to B, with the helicopter taking off from the ground, running the flight software that it will be running on board, simulating the images that the navigation camera takes of the ground below as it flies, feeding that back into the flight software, and then controlling it.
To what extent can simulation really compensate for the kinds of physical testing that you can’t do on Earth?
It gives you a few different possibilities. We can take certain tests on Earth where we replicate key elements of the environment, like the atmosphere or the visual surroundings for example, and you can validate your simulation on those parameters that you can test on Earth. Then, you can combine those things in simulation, which gives you the ability to set up arbitrary scenarios and do lots and lots of tests. We can Monte Carlo things, we can do a flight a thousand times in a row, with small perturbations of various parameters and tease out what our sensitivities are to those things. And those are the kinds of things that you can't do with physical tests, both because you can't fully replicate the environment and also because of the resources that would be required to do the same thing a thousand times in a row.
Because there are limits to the physical testing we can do on Earth, there are elements where we know there's more uncertainty. On those aspects where the uncertainty is high, we tried to build in enough margin that we can handle a range of things. And simulation gives you the ability to then maybe play with those parameters, and put them at their outer limits, and test them beyond where the real parameters are going to be to make sure that you have robustness even in those extreme cases.
How do you make sure you’re not relying on simulation too much, especially since in some ways it’s your only option?
It’s about anchoring it in real data, and we’ve done a lot of that with our physical testing. I think what you’re referring to is making your simulation too perfect, and we’re careful to model the things that matter. For example, the simulated sensors that we use have realistic levels of simulated noise and bias in them, the navigation camera images have realistic levels of degradation, we have realistic disturbances from wind gusts. If you don’t properly account for those things, then you’re missing important details. So, we try to be as accurate as we can, and to capture that by overbounding in areas where we have a high degree of uncertainty.
What kinds of simulated challenges have you put the Mars helicopter through, and how do you decide how far to push those challenges?
One example is that we can simulate going over rougher terrain. We can push that, and see how far we can go and still have the helicopter behave the way that we want it to. Or we can inject levels of noise that maybe the real sensors don't see, but you want to just see how far you can push things and make sure that it's still robust.
Where we put the limits on this and what we consider to be realistic is often a challenge. We consider this on a case by case basis—if you have a sensor that you're dealing with, you try to do testing with it to characterize it and understand its performance as much as possible, and you build a level of confidence in it that allows you to find the proper balance.
When it comes to things like terrain roughness, it's a little bit of a different thing, because we're actually picking where we're flying the helicopter. We have made that choice, and we know what the terrain looks like around us, so we don’t have to wonder about that anymore.
Image: NASA/JPL-Caltech/University of Arizona
Satellite image of the Ingenuity flight area.
The way that we’re trying to approach this operationally is that we should be done with the engineering at this point. We’re not depending on going back and resimulating things, other than a few checks here and there.
Are there any examples of things you learned as part of the simulation process that resulted in changes to the hardware or mission?
You know, it’s been a journey. One of the early things that we discovered as part of modeling the helicopter was that the rotor dynamics were quite different for a helicopter on Mars, in particular with respect to how the rotor responds to the up and down bending of the blades because they’re not perfectly rigid. That motion is a very important influence on the overall flight dynamics of the helicopter, and what we discovered as we started modeling was that this motion is damped much less on Mars. Under-damped oscillatory things like that, you kind of figure might pose a control issue, and that is the case here: if you just naively design it as you might a helicopter on Earth, without taking this into account, you could have a system where the response to control inputs becomes very sluggish. So that required changes to the vehicle design from some of the very early concepts, and it led us to make a rotor that’s extremely light and rigid.
The design cycle for the Mars helicopter—it’s not like we could just build something and take it out to the back yard and try it and then come back and tweak it if it doesn’t work. It’s a much bigger effort to build something and develop a test program where you have to use a vacuum chamber to test it. So you really want to get as close as possible up front, on your first iteration, and not have to go back to the drawing board on the basic things.
So how close were you able to get on your first iteration of the helicopter design?
[This video shows] a very early demo which was done more or less just assuming that things were going to behave as they would on Earth, and that we’d be able to fly in a Martian atmosphere just spinning the rotor faster and having a very light helicopter. We were basically just trying to demonstrate that we could produce enough lift. You can see the helicopter hopping around, with someone trying to joystick it, but it turned out to be very hard to control. This was prior to doing any of the modeling that I talked about earlier. But once we started seriously focusing on the modeling and simulation, we then went on to build a prototype vehicle which had a full-size rotor that’s very close to the rotor that will be flying on Mars. One difference is that prototype had cyclic control only on the lower rotor, and later we added cyclic control on the upper rotor as well, and that decision was informed in large part by the work we did in simulation—we’d put in the kinds of disturbances that we thought we might see on Mars, and decided that we needed to have the extra control authority.
How much room do you think there is for improvement in simulation, and how could that help you in the future?
The tools that we have were definitely sufficient for doing the job that we needed to do in terms of building a helicopter that can fly on Mars. But simulation is a compute-intensive thing, and so I think there’s definitely room for higher fidelity simulation if you have the compute power to do so. For a future Mars helicopter, you could get some benefits by more closely coupling together high-fidelity aerodynamic models with larger multi-body models, and doing that in a fast way, where you can iterate quickly. There’s certainly more potential for optimizing things.
Photo: NASA/JPL-Caltech
Ingenuity preparing for flight.
Watching Ingenuity’s first flight take place will likely be much like watching the Perseverance landing—we’ll be able to follow along with the Ingenuity team while they send commands to the helicopter and receive data back, although the time delay will mean that any kind of direct control won’t be possible. If everything goes the way it’s supposed to, there will hopefully be some preliminary telemetry from Ingenuity saying so, but it sounds like we’ll likely have to wait until April 12 before we get pictures or video of the flight itself.
Because Mars doesn’t care what time it is on Earth, the flight will actually be taking place very early on April 12, with the JPL Mission Control livestream starting at 3:30 a.m. EDT (12:30 a.m. PDT). Details are here. Continue reading →
Posted in Human Robots
#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
#438012 Video Friday: These Robots Have Made 1 ...
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!):
HRI 2021 – March 8-11, 2021 – [Online Conference]
RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
Let us know if you have suggestions for next week, and enjoy today's videos.
We're proud to announce Starship Delivery Robots have now completed 1,000,000 autonomous deliveries around the world. We were unsure where the one millionth delivery was going to take place, as there are around 15-20 service areas open globally, all with robots doing deliveries every minute. In the end it took place at Bowling Green, Ohio, to a student called Annika Keeton who is a freshman studying pre-health Biology at BGSU. Annika is now part of Starship’s history!
[ Starship ]
I adore this little DIY walking robot- with modular feet and little dials to let you easily adjust the walking parameters, it's an affordable kit that's way more nuanced than most.
It's called Bakiwi, and it costs €95. A squee cover made from feathers or fur is an extra €17. Here's a more serious look at what it can do:
[ Bakiwi ]
Thanks Oswald!
Savva Morozov, an AeroAstro junior, works on autonomous navigation for the MIT mini cheetah robot and reflects on the value of a crowded Infinite Corridor.
[ MIT ]
The world's most advanced haptic feedback gloves just got a huge upgrade! HaptX Gloves DK2 achieves a level of realism that other haptic devices can't match. Whether you’re training your workforce, designing a new product, or controlling robots from a distance, HaptX Gloves make it feel real.
They're the only gloves with true-contact haptics, with patented technology that displace your skin the same way a real object would. With 133 points of tactile feedback per hand, for full palm and fingertip coverage. HaptX Gloves DK2 feature the industry's most powerful force feedback, ~2X the strength of other force feedback gloves. They're also the most accurate motion tracking gloves, with 30 tracked degrees of freedom, sub-millimeter precision, no perceivable latency, and no occlusion.
[ HaptX ]
Yardroid is an outdoor robot “guided by computer vision and artificial intelligence” that seems like it can do almost everything.
These are a lot of autonomous capabilities, but so far, we've only seen the video. So, best not to get too excited until we know more about how it works.
[ Yardroid ]
Thanks Dan!
Since as far as we know, Pepper can't spread COVID, it had a busy year.
I somehow missed seeing that chimpanzee magic show, but here it is:
[ Simon Pierro ] via [ SoftBank Robotics ]
In spite of the pandemic, Professor Hod Lipson’s Robotics Studio persevered and even thrived— learning to work on global teams, to develop protocols for sharing blueprints and code, and to test, evaluate, and refine their designs remotely. Equipped with a 3D printer and a kit of electronics prototyping equipment, our students engineered bipedal robots that were conceptualized, fabricated, programmed, and endlessly iterated around the globe in bedrooms, kitchens, backyards, and any other makeshift laboratory you can imagine.
[ Hod Lipson ]
Thanks Fan!
We all know how much quadrupeds love ice!
[ Ghost Robotics ]
We took the opportunity of the last storm to put the Warthog in the snow of Université Laval. Enjoy!
[ Norlab ]
They've got a long way to go, but autonomous indoor firefighting drones seem like a fantastic idea.
[ CTU ]
Individual manipulators are limited by their vertical total load capacity. This places a fundamental limit on the weight of loads that a single manipulator can move. Cooperative manipulation with two arms has the potential to increase the net weight capacity of the overall system. However, it is critical that proper load sharing takes place between the two arms. In this work, we outline a method that utilizes mechanical intelligence in the form of a whiffletree.
And your word of the day is whiffletree, which is “a mechanism to distribute force evenly through linkages.”
[ DART Lab ]
Thanks Raymond!
Some highlights of robotic projects at FZI in 2020, all using ROS.
[ FZI ]
Thanks Fan!
iRobot CEO Colin Angle threatens my job by sharing some cool robots.
[ iRobot ]
A fascinating new talk from Henry Evans on robotic caregivers.
[ HRL ]
The ANA Avatar XPRIZE semifinals selection submission for Team AVATRINA. The setting is a mock clinic, with the patient sitting on a wheelchair and nurse having completed an initial intake. Avatar enters the room controlled by operator (Doctor). A rolling tray table with medical supplies (stethoscope, pulse oximeter, digital thermometer, oxygen mask, oxygen tube) is by the patient’s side. Demonstrates head tracking, stereo vision, fine manipulation, bimanual manipulation, safe impedance control, and navigation.
[ Team AVATRINA ]
This five year old talk from Mikell Taylor, who wrote for us a while back and is now at Amazon Robotics, is entitled “Nobody Cares About Your Robot.” For better or worse, it really doesn't sound like it was written five years ago.
Robotics for the consumer market – Mikell Taylor from Scott Handsaker on Vimeo.
[ Mikell Taylor ]
Fall River Community Media presents this wonderful guy talking about his love of antique robot toys.
If you enjoy this kind of slow media, Fall River also has weekly Hot Dogs Cool Cats adoption profiles that are super relaxing to watch.
[ YouTube ] Continue reading →
Posted in Human Robots
#437884 Hyundai Buys Boston Dynamics for Nearly ...
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
#437880 SoftBank sells controlling stake in ...
Japan's SoftBank Group will sell an 80 percent stake in robotics firm Boston Dynamics to Hyundai, the trio said Friday, in a deal that values the US company at $1.1 billion. Continue reading →
Posted in Human Robots