Marc Raibert: Boston Dynamics and the Future of Robotics | Lex Fridman Podcast #412

So big dog became LS3, which is the big load carrying one.

Just, just a quick pause. It can carry 400 pounds.

It was designed to carry 400, but we had it carrying about a thousand pounds at one time.

Of course you did just.

We had, we had one carrying the other one. We had two of them, so we had one carrying the other one.

So one of the things that stands out about the robots Boston Dynamics have created is how beautiful the movement is, how natural the walking is. And running is, even flipping is, throwing is. So maybe you can talk about what's involved in making it look natural.

Well, I think having good hardware is part of the story, and people who think you don't need to innovate hardware anymore are wrong.

The following is a conversation with Mark Reibert, a legendary roboticist, founder and longtime CEO of Boston Dynamics, and recently the executive director of the newly created Boston Dynamics AI Institute that focuses on research and the cutting edge on creating future generations of robots that are far better than anything that exists today. He has been leading the creation of incredible legged robots for over 40 years at CMU, at MIT, the legendary MIT leg lab, and then of course, Boston Dynamics with amazing robots like Big Dog, Atlas, Spot and Handle. This was a big honor and pleasure for me. This is the Lex Friedman podcast to support it. Please check out our sponsors in the description. And now, dear friends, here's Mark Reibert. When did you first fall in love with robotics?

Well, I was always a builder. From a young age, I was lucky. My father was a frustrated engineer. And by that I mean he wanted to be an aerospace engineer, but his mom from the old country thought that that would be like a grease monkey. And so she said no. So he became an accountant. But the result of that was our basement was always full of tools and equipment and electronics. And, you know, from a young age, I would watch him assembling a kit, an IKO kit or something like that. I still have a couple of his old IKO kits. But it was really during graduate school when I followed a professor back from class. It was Bertolt Horn at mit, and I was taking an interim class, it's IAP, Independent Activities period. And I followed him back to his lab and on the table was a VIK arm robot arm, taken apart in probably a thousand pieces. And when I saw that, from that day on, I was a roboticist. Do you remember the year 1974?

1974. So there's just this arm in pieces. And you saw the pieces and you saw in, in your vision the arm when it's put back together and the possibilities that holds.

Somehow it spurred my imagination. I was in the Brain and Cognitive sciences department as a graduate student doing neurophysiology. I'd been an electrical engineer as an undergrad at Northeastern. And the neurophysiology wasn't really working for me. It wasn't conceptual enough. I couldn't see really how by looking at single neurons, you were going to get to a place where you could understand control systems or thought or anything like that. And the AI lab was always an appealing. This was before CSAIL, right? This was in the 70s. So the AI lab was always an appealing idea. And so when I went back to the AI lab following him and I saw the arm, I just thought, this is it.

That's so interesting, the tension between the BCS brain cognitive science approach to understanding intelligence and the robotics approach to understanding intelligence.

Well, BCS has now morphed a bit, right? They have the center for Brains, Minds and Machines, which is trying to bridge that gap. And even when I was there, David Marr was in the AI lab. David Marr had models of the brain that were appealing both to biologists, but also to computer people. So he was a visitor in the AI lab at the time. And I guess he became full time there. So that was the first time a bridge was made between those two groups. Then the bridge kind of went away. And then there was another time in the 80s. And then recently, the last five or so years, there's been a stronger connection.

You said you were always kind of a builder. What stands out to you in memory of a thing you've built? Maybe a trivial thing that just kind of inspired you in the possibilities that this direction of work might hold?

I mean, we were just doing gadgets when we were kids. You know, I had a friend, we were taking, you know, the. I don't know if everybody remembers, but fluorescent lights had this little aluminum cylinder. I can't even remember what it's called now, that you needed a starter, I think it was. And we would take those apart, fill them with match heads, put a tail on it, and make it into little rockets.

So it wasn't always about function. It was.

Well, rocket was pretty much functional.

I guess that is pretty functional. But I guess that is a question. How much was it about function versus just creating something cool?

I think it's still a balance between those two. There was a time, though, when I was. I guess I was probably already a professor or maybe late in graduate school when I thought that function was everything. And that mobility, dexterity, perception and intelligence, those are sort of the key functionalities for robotics, that that's what mattered and nothing else mattered. And I even had kind of this platonic ideal that a robot, if you just looked at a robot and it wasn't doing anything, it would look like a pile of junk, which a lot of my robots looked like in those days. But then when it started moving, you'd get the idea that it had some kind of life or some kind of interest in its movement. And I think we purposely even designed the machines, not worrying about the aesthetics of the structure itself. But then it turns out that the aesthetics of the thing itself add and combine with the lifelike things that the robots can do. But the heart of it is making them do things that are interesting.

So one of the things that underlies a lot of your work is that the robots you create, the systems you have created for over 40 years now, have a kind of they're not cautious. So a lot of robots that people know about move about this world very cautiously, carefully, very afraid of the world. A lot of the robots you build, especially in the early days, were very aggressive, under actuated, they're hopping, they're wild, moving quickly. So is there a philosophy underlying that?

Well, let me tell you about how I got started on legs at all. When I was still a graduate student, I went to a conference. It was a biological legged locomotion conference, I think it was in Philadelphia. So it was all biomechanics people, researchers who would look at muscle and maybe neurons and things like that. They weren't so much computational people, but they were more biomechanics. And maybe there were a thousand people there. And I went to a talk, one of the talks, all the talks were about the body of either animals or people and respiration, things like that. But one talk was by a robotics guy and he showed a six legged robot that walked very slowly. It always had at least three feet on the ground. So it worked like a table or a chair with tripod stability. And it moved really slowly. And I just looked at that and said, wow, that's wrong. That's not anything like how people and animals work. Because we bounce and fly, we have to predict what's going to happen in order to keep our balance. When we're taking a running step or something like that, we use the springiness in our legs, our muscles and our tendons and things like that as part of the story. The energy circulates. We don't just throw it away every time. So I'm not sure I understood all that when I first thought, but I definitely got inspired to say let's try the opposite. And I didn't have a clue as to how to make a hopping robot work. Not balance in 3D. In fact, when I started it was all just about the energy of bouncing. And I was going to have a springy thing in the leg and some actuator so that you could get an energy regime going of bouncing. And the idea that balance was an important part of it didn't come until a little later. And then, you know, Mike made the one legged the pogo stick robots. Now I think that we need to do that in manipulation. If you look at robot manipulation, we've been working, we a community has been working on it for 50 years. We're nowhere near human levels of manipulation. I mean we can, you know, it's come along, but I think it's all too safe. And I think trying to break out of that safety thing of static grasping. If you look at a lot of work that goes on, it's about the geometry of the part. And then you figure out how to move your hand so that you can position it with respect to that and then you grasp it carefully and then you move it. Well, that's not anything like how people and animals work. We juggle in our hands, we hug multiple objects and can sort them. So now to be fair, being more aggressive is going to mean things aren't going to work very well for a while. So it's a longer term approach to the problem. And that's just theory. Now maybe that won't pay off, but that's sort of how I'm trying to think about it. Trying to encourage our group to go at it.

Well, yeah, I mean we'll talk about what it means to what is the actual thing we're trying to optimize. And for a robot, you know, sometimes, especially with human robot interaction, maybe flaws is a good thing. Perfection is not necessarily the right thing to be chasing. Just like you said, maybe being good at fumbling an object, being good at fumbling might be the right thing to optimize versus perfect modeling of the object and perfect movement of the arm to grasp that object. Because maybe perfection is not supposed to exist in the real world.

I don't know if you know my friend Matt Mason, he who is the director of the Robotics Institute at Carnegie Mellon and we go back to graduate school together, but he analyzed a movie of Julia Childs doing a cooking thing and she did. I think he said something like there were 40 different ways that she handled a thing and none of them was grasping. She would nudge, roll, flatten with her knife, things like that, and none of them was grasping.

So, okay, let's go back to the early days. First of all, you've created and led the Leg Lab, the legendary Leg Lab at mit. So what was that first hopping robot?

But first of all, the Leg Lab actually started at Carnegie Mellon.

Carnegie Mellon.

So I was a professor there starting in 1980 to about 1986. And so that's where the first hopping machines were built. Starting, I guess we got the first one working in about 1982, something like that. That was a simplified one. Then we got a three dimensional one in 1983. The quadruped that we built at the Leg Lab, the first version was built in about 1984, five and really only got going about 86 or so and took years of development to get it to.

Let's just pause here for people who don't know. I'm talking to Mark Raibert, founder of Boston Dynamics. But before that you were a professor developing some of the most incredible robots for 15 years. And before that of course a grad student and all that. So you've been doing this for a really long time. So you like skipped over this. But like go, go to the first hopping robot. There's videos of some of this. I mean these are incredible robots. He talked about the first, the very first step was to get a thing hopping up and down, right? And then you realized, well, balancing is a thing you should care about and it's actually a solvable problem. So can you just go through how to create that robot? What was involved in creating that robot?

Well, I'm going to start on the, not the technical side, but the, I guess we could call it the motivational side or the funding side. So before Carnegie Mellon, I was actually at JPL at the Jet Propulsion Lab for three years. And while I was there I connected up with Ivan Sutherland, who is sometimes regarded as the father of computer graphics because of work he did both at MIT and then University of Utah and Evans and Sutherland. Anyway, I got to know him and at one point he said he encouraged me to do some kind of project at Caltech even though I was at jpl. Those are kind of related institutions. And so I thought about it and I made up a list of three possible projects and I purposely made the top one and the bottom one really boring sounding. And in the middle I put pogo stick robot. And when he looked at it, Ivan is A brilliant, brilliant guy, brilliant engineer and real cultivator of people. He looked at it and knew right away what the thing that was worth doing. And so he had an endowed chair. So he had about that he gave me to build a first model, which I went to the shop and with my own hands kind of made a first model which didn't work and was just a beginning shot at it. And Ivan and I took that to Washington. And in those days, you could just walk into DARPA and walk down the hallway and see who's there. Ivan, who had been there in his previous life. And so we walked around and we looked in the offices. Of course, I didn't know anything. I was basically a kid. But Ivan knew his way around. And we found Craig Fields in his office. Craig later became the director of darpa, but in those days he was a program manager. And so we went in. I had a little Samsonite suitcase which we opened, and it had just the skeleton of this one legged hopping robot. And we showed it to him, and you could almost see the drool going down his chin of excitement. And he sent me $250,000. He said, okay, I want to fund this. And I was between institutions. I was just about to leave JPL and I hadn't decided yet where I was going next. And then when I landed at CMU, he sent $250,000, which in 1980 was a lot of research money.

Did you see the possibility of where this is going? Why this is an important problem? No, the balancing. I mean, it's legged. It has to do with legged locomotion. I mean, it has to do with all these problems that, that, that are the human body solves. When we're walking, for example, like, all the fundamentals are there.

Yeah, I mean, I think that was the motivation to try and get more at the fundamentals of how animals work. But the idea that it would result in, you know, machines that were anything like, practical like we're making now, that. That wasn't anywhere in my head. No. You know, as an academic, I was mostly just trying to do the next thing, you know, make some progress, impress my colleagues if I could, and have fun. And have fun.

Pogo stick robot. Pogo stick robot. So what was on the technical side? What are the. Some of the challenges of getting up, getting to the point where we saw, like in the video, the pogo stick robot that's actually successfully hopping and then eventually doing flips and all this kind of stuff?

Well, in the very early days, I needed some better engineering than I could do myself, and I hired Ben Brown. We each had our way of contributing to the design, and we came up with a thing that could start to work. I had some stupid ideas about how the actuation system should work, and we sorted that out. It wasn't that hard to make it balanced once you get the physical machine to be working well enough and have enough control over the degrees of freedom. And then we, very quickly, we started out by having it floating on an inclined air table, and then that only gave us, like, six foot of travel. So once it started working, we switched to a thing that could run around the room on another device. It's hard to explain these without you seeing them, but you probably know what I'm talking about. A planarizer. And. And then the next big step was to make it work in 3D, which. That was really the scary part with these simple things. You know, people had inverted pendulums at the time for years, and they could control them by driving a cart back and forth. But could you make it work in three dimensions while it's bouncing and all that? But it turned out not to be that hard to do, at least at the level of performance we achieved at the time.

So, okay, you mentioned inverted pendulum, but, like, can you explain how a hopping stick in 3D can balance itself?

Yes.

What does the actuation look like?

You know, the simple story is that there's three things going on. There's something making it bounce. And, you know, we had a system that was estimating how high the robot was off the ground. And using that, you know, there's energy that can be in three places in a pogo stick. One is in the spring, one is in the altitude, and the other is in the velocity. And so when at the top of the hop, it's all in the height. And so you could just measure how high you're going and thereby have an idea of a lot about the cycle. And you could decide whether to put more energy in or less. So that is one element. Then there's a part that you decide where to put the foot. And if you think when you're landing on the ground with respect to the center of mass. So if you think of a pole vaulter, the key thing the pole vaulter has to do is get its body to the right place. When the pole gets stuck, if they're too far forward, they kind of get thrown backwards. If they're too far back, they go over. And what they need to do is get it so that they go mostly up to get over the Thing, and, you know, high jumpers is the same kind of thing. So there's a calculation about where to put the foot, and we did something relatively simple. And then there's a third part to keep the body at an attitude that's upright, because if it gets too far, you could hop and just keep rotating around. But if it gets too far, then you run out of motion of the joints at the hips. So you have to do that. And we did that by applying a torque between the legs and the body. Every time the foot's on the ground, you only can do it while the foot's on the ground, in the air. The physics don't work out.

How far does it have to tilt before it's too late to be able to balance itself or it's impossible to balance itself, correct itself?

Well, you're asking an interesting question, because in those days, we didn't actually optimize things, and they probably could have gone much further than we did and then had higher performance. And we just kind of got a sketch of a solution and worked on that. And then in years since, some people working for us, some people working for others people came up with all kinds of equations or algorithms for how to do a better job, be able to go faster. One of my students worked on getting things to go faster. Another one worked on climbing over obstacles. Because when you're running on the open ground, it's one thing if you're running, like up a stair. You have to adjust where you are. Otherwise things don't work out right. You land your foot on the edge of the step. So there's other degrees of freedom to control if you're getting to more realistic, practical situations.

I think it's really interesting to ask about the early days, because believing in yourself, believing that there's something interesting here, and then you mentioned finding somebody else. Ben Brown, what's that like finding other people with whom you can build this crazy idea and actually make it work?

Probably the smartest thing I ever did is to find the other people. I mean, when I look at it now, I look at Boston Dynamics and all the really excellent engineering there, you know, people who really make stuff work, you know, I'm. I'm only the. The dreamer.

So when you talk about pogo stick, robot or legged robots, whether it's quadrupeds or humanoid robots, did people doubt that this is possible? Did you experience a lot of people around you? Kind of.

I don't. I don't know if they doubted whether it was possible, but I think they thought it was a waste of time.

Oh, it's not even an interesting problem.

I think for a lot of people, you know, people who were. I think it's been both, though. Some people, I think I felt like they were saying, oh, why are you wasting your time on this stupid problem? But then I've been at many things where people have told me it's been an inspiration to go out and attack these harder things. And I think it has turned out, I think legged locomotion has turned out to be a useful thing.

Did you ever have like doubt about bringing Atlas to life, for example, or with Big Dog just every step of the way? Did you have doubt? Like, this is too hard of a problem?

I mean, at first I wasn't an enthusiast for the humanoids because again, it goes back to saying what's the functionality? And the form wasn't as important as the functionality. And also there's an aspect to humanoid robots that's all about the cosmetics, where there isn't really other functionality. And that kind of is off putting for me as a roboticist. I think the functionality really matters. So probably that's why I avoided humanoid robots to start with. But I'll tell you now, after we started working on them, you could see that the connection and the impact with, with other people, whether they're laypeople or even other technical people, there's a. There's a special thing that goes on. Even though most of the humanoid robots aren't that much like a person.

But we anthropomorphize and we see the humanity. But also, like with, with Spot, you can see not the humanity but the what. Whatever we find compelling about social interaction is there in Spot as well, I'll tell you.

You know, I go around giving talks and take Spot to a lot of them and it's amazing. The media likes to say that they're terrifying and that people are afraid, and YouTube commenters like to say that it's frightening. But when you take a spot out there now, maybe it's self selecting, but you get a crowd of people who want to take pictures, want to pose for selfies, want to operate the robot, want to pet it, want to put clothes on it, it's amazing.

Yeah, I love Spot. So if we move around history a little bit. So you said, I think in the early days of Boston Dynamics that you quietly worked on making a running version of ibo.

Yeah, yeah.

Sony's Robot Dog. Yeah, it's just an interesting little tidbit of history for me. What stands out to your Memory from that task. For people who don't know that little dog robot moves slowly. How did that become big dog? What was involved there? What was the dance between how do we make this cute little dog versus a thing that can actually carry a lot of payload and move fast and stuff, stuff like that.

What the connection was is that at that point, Boston Dynamics was mostly a physics based simulation company. So when I left MIT to start Boston Dynamics, there was a few years of overlap, but the concept wasn't to start a robot company. The concept was to use this dynamic simulation tool that we developed to do robotics for other things. But working with Sony, we got back into robotics by doing the AIBO runner by we programmed, we made some tools for programming Curio, which was a small humanoid, this big, that could do some dancing and other kinds of fun stuff. And I don't think it ever reached the market, even though they did show it. When I look back, I say we got us back where we belonged.

Yeah, you rediscovered the soul of the company.

That's right.

And so from there it was always about robots. So you started Boston Dynamics in 1992.

Right.

Some fond memories from the early days.

One of the robots that we built wasn't actually a robot. It was a surgical simulator, but it had force feedback. So it had all the techniques of robotics. And you looked down into this mirror, it actually was, and it looked like you were looking down onto the body you were working on. Your hands were underneath the mirror. So there were where you were looking and you had tools in your hands that were connected up to these force feedback devices made by another MIT spin out, Sensible technologies. So they made the force feedback device. We attached the tools and we wrote all the software and did all the graphics. So we had 3D computer graphics. It was in the old days. This was in the late 90s when you had a Silicon Graphics computer that was about this big. It was the heater in the office basically. And, and we were doing surgical operations, anastomosis, which was stitching tubes together, tubes like blood vessels or other things in their body. And you could feel and you could see the tissues move. And it was really exciting. And the idea was to make a trainer to teach surgeons how to do stuff. We built a scoring system because we interviewed surgeons that told us what you're supposed to do and what you're not supposed to do. You're not supposed to tear the tissue, you're not supposed to touch it in any place except for where you're trying to eng. There were a bunch of Rules. So we built this thing and took it to a trade show, a surgical trade show. And the surgeons were practically lined up. Well, we kept a score and we posted their scores like on a video game. And those guys are so competitive that they really, really love doing it. And they would come around and they see someone's score was higher there, so they would come back. But we figured out shortly after that we thought surgeons were going to pay us to get trained on these things. And the surgeons thought we should pay them in order to, so they could teach us about the thing. And there was no money from the surgeons. And we looked at it and thought, well, maybe we could sell it to hospitals that would teach, train their surgeons. And then we said, well, we're this. At the time we were probably a 12 person company or maybe 15 people, I don't remember. There's no way we could go after a marketing activity. You know, the company was all bootstrapped in those years. We never had investors until Google bought us, which was after 20 years. So we didn't have any resources to go after hospitals. So we at one, sort of, at one day, Rob and I were looking at that and we said, we built another simulator for knee arthroscopy and we said, this isn't going to work. And we killed it and we moved on. And that was really a milestone in the company because we, you know, we sort of understood who we were and what would work and what wouldn't. Even though technically it was really a fascinating thing.

What was that meeting like? Were you just like sitting at a table? You know what, probably we're going to pivot completely. We're going to let go of this thing we put so much hard work into and then go back to the thing it just came from.

It just always felt right once we did it, you know, just look at.

Each other and said, let's build robots.

Yeah.

What was the first robot you built under the flag of Boston Dynamics Big Dog?

Well, there was the AIBO runner, but it wasn't even a whole robot. It was just legs that we, we took off the legs on AIBO's and attached legs we'd made. And, you know, we got that working and showed it to the SONY people. We worked pretty closely with Sony in those years. One of the interesting things is that it was before the Internet and zoom and anything like that. So we had six ISDN lines installed and we would have a telecon every week that worked at very low frame rate, something like 10 hertz, you know, English across the boundary with Japan was a challenge. Trying to understand what each of us was saying and have meetings every week for several years doing that. And it was a pleasure working with them. They were really supporters, they seemed to like us and what we were doing. That was the real transition from us being a simulation company into being a robotics company again.

It was a quadruped. The legs were four legs or two legs.

Yeah. No, four legs. Yeah.

And what did you learn from that experience of building basically a fast moving quadruped?

Mostly we learned that something that small, it doesn't look very exciting when it's running, it's like it's scampering. And you had to watch a slow mo for it to look like it was interesting. If you watch it fast, it was just like a.

That's funny.

One of my things was to show stuff in video, even from the very early days of the hopping machines. And so I was always focused on how's this going to look through the viewfinder. And running Aibo didn't look so cool through the viewfinder.

So what came next in terms of what was a big next milestone in terms of a robot you built?

I mean, you got to say that Big Dog was sort of put us on the map and got our heads really pulled together. We scaled up the company. Big Dog was the result of Alan Rudolph at DARPA starting a biodynotics program. And he put out a request for proposals. And I think there were 42 proposals written and three got funded. One was Big Dog, one was a climbing robot. Rise. And you know, that put things in motion. We hired Martin Buehler. He was a professor in Montreal at McGill. He was incredibly important for getting Big Dog out of the lab and into the mud, which was a key step to really be willing to go out there and, and build it, break it, fix it, which is sort of one of our mottos at the company.

So testing in the real world for people who don't know Big Dog, maybe you can correct me, but it's a big quadruped, four leg robot. It looks big, could probably carry a lot of weight. Not the most weight that Boston Dynamics have built, but a lot.

Well, it's the first thing that worked. So let's see if we go back to the leg lab. We built a quadruped that could do many of the things that Big Dog did, but it had a hydraulic pump sitting in the room with hoses connected to the robot. It had a VAX computer in the next room. It needed its own room because it was this giant thing with air conditioning. And it had this very complicated bus connected to the robot. And the robot itself just had the actuators. It had gyroscopes for sensing and some other sensors, but all the power and computing was off board. Big Dog had all that stuff integrated on the platform. It had a gasoline engine for power, which was a very complicated thing to undertake. It had to convert the rotation of the engine into hydraulic power, which is how we actuated it. So there was a lot of learning just on building the physical robot and the system integration for that, and then there was the controls of it.

So for Big Dog, it brought it all together onto one platform.

Right.

And then. So you could. You can.

You could take it out in the woods.

Yeah. And you did?

We did. We spent a lot of time down at the Marine Corps base in Quantico where there was a trail called the Guadalcanal Trail. And our milestone that DARPA had specified was that we could go on this one particular trail that involved, you know, a lot of challenge. And we spent a lot of time. Our team spent a lot of time down there.

Those were fun days hiking with the robot. So what did you learn about, like, what it takes to balance a robot like that on a trail? On a hiking trail in the woods, basically. Forget the woods, just the real world. That's the big leap into testing in the real world.

Yeah. As challenging as the woods were, working inside of a home or in an office is really harder because when you're in the woods, you can actually take any path up the hill. All you have to do is avoid the obstacles. There's no such thing as damaging the woods, at least to first order. Whereas if you're in a house, you can't leave scuff marks. You can't bang into the walls. The robots aren't very comfortable bumping into the walls, especially in the early days. So I think those were actually bigger challenges once we faced them, it was mostly getting the systems to work well enough to gather the hardware systems to work and the controls. In those days, we did have a human operator who did all the visual perception going up the Guadalcanal Trail. So there was an operator who was right there who was very skilled at. Even though the robot was balancing itself and placing its own feet, if the operator didn't do the right thing, it wouldn't go. But years later, we went back with one of the electric, the precursor to spot, and we had advanced the controls and everything so much that an amateur, complete amateur, could operate the robot. The first time, up and down and up and down. Whereas it had taken us years to get there in the previous robot.

So if you fast forward, Big dog eventually became spot.

So big dog became LS3, which is the big load carrying one.

Just, just a quick pause. It can carry £400.

It was designed to carry 400, but we had it carrying about a thousand pounds at one time.

Of course you did.

Just make sure we had one carrying the other one. We had two of them, so we had one carrying the other one. There's a little clip of that. We should put that out somewhere. That's from like 20 years ago, but wow. Wow.

And it can go for very long distances. You can travel 20 miles.

Yeah, gasoline.

Gasoline, yeah. And that, that event. Okay, sorry. So LS3, then what. How did that lead to Spot?

So big dog and LS3 had engine power and hydraulic actuation. Then we made a robot that was electric power. So there's a battery driving a motor, driving a pump, but still hydraulic actuation. Larry sort of asked us, could you make something that weighed 60 pounds that would not be so intimidating if you had it in a house where there were people? And that was the inspiration behind the Spot, pretty much as it exists today. We did a prototype the same size that was the first all electric, non hydraulic robot.

What was the conversation with Larry Page like about? So here's a guy that kind of is very product focused and can see a vision for like what the future holds. That's just interesting. Kind of aside, what was the brainstorm about the future of robotics with him? Like?

I mean, it was almost as simple as what I just said. You know, we were having a meeting. He said, yeah, geez, you know, do you think you could make a smaller one that wouldn't be so intimidating like a big dog? Yeah, if it was in your house. And I said, yeah, we could do that. And we started and did.

Is there a lot of technical challenges to go from hydraulic to electric?

You know, I had been in love with hydraulics and still love hydraulics. You know, it's a great technology. It's too bad that somehow the world out there looks at it like it's old fashioned or that it's icky. And it's true that you do. It is very hard to keep it from having some amount of dripping from time to time. But if you look at the performance, you know, how strong you can get in a lightweight package. And of course, we did a huge amount of innovation, most of hydraulic control, that is the valve that controls the flow of oil had been designed in the 50s for airplanes. It had been made robust enough, safe enough that you could count on it, so that humans could fly in airplanes. And very little innovation had happened. You know, that might not be fair to the people who make the valves. I'm sure that they did innovate, but the basic design had stayed the same and there was so much more you could do. And so our engineers designed valves, the ones that are in Atlas, for instance, that had new kinds of circuits. They sort of did some of the computing that could get you much more efficient use. They were much smaller and lighter, so the whole robot could be smaller and lighter. We made a hydraulic power supply that had a bunch of components integrated in this tiny package. It's about this big, the size of a football, weighs 5kg and it produces 5kW of power. Of course, it has to have a battery operating, but it's got a motor, a pump, filters, heat exchanger to keep it cool, some valves, all in this tiny little package. So hydraulics could still have a ways to go.

One of the things that stands out about the robots Boston Dynamics have created is how beautiful the movement is, how natural the walking is and running is, even flipping with throwing is. So maybe you can talk about what's involved in making it look natural.

Well, I think having good hardware is part of the story. And people who think you don't need to innovate hardware anymore are wrong, in my opinion. So I think one of the things, certainly in the early years for me, taking a dynamic approach where you think about what's the evolution of the motion of the thing going to be in the future, and having a prediction of that that's used at the time that you're giving signals to it, as opposed to it all being servoing, which is servoing is sort of backward looking. It says, okay, where am I now? I'm going to try and adjust for that, but you really need to think about what's coming.

So how far ahead do you have to look in time?

It's interesting, I think that the number is only a couple of seconds for spot. So there's a limited horizon type approach where you're recalculating, assuming what's going to happen in the next second or second and a half. And then you keep iterating at the next, even though a tenth of a second later you'll say, okay, let's do that again and see what's happening. And you're looking at what the obstacles are, where the Feet are going to be placed. How to, you know, you have to coordinate a lot of things. If you have obstacles and you're balancing at the same time, and it's that limited horizon type calculation that's doing a lot of that. But if you're doing something like a somersault, you're looking out a lot further, right? If you want to stick the landing, you have to get, you have to at the time of launch have momentum and rotation, all those things coordinated so that a landing is within reach.

How hard is it to stick a landing? I mean it's very much under actuated like you. Once you've in the air, you don't have as much control about anything. So how hard is it to get that to work? First of all, did flips with a hopping robot.

If you look at the first time we ever made a robot do a somersault, it was in a planar robot. You know, it had a boom. So it was restricted to the surface of a sphere, we call that planar. So it could move fore and aft, it could go up and down and it could rotate. And so the calculation of what you need to do to get a, to stick a landing isn't all that complicated. You have to look at, you know, you have to get time to make the rotation. So how hard you jump, how high you jump gives you time. You look at how quickly you can rotate. And so if you get those two right, then when you land, you have the feet in the right place and you have to get rid of all that rotational and linear momentum. But that's not too hard to figure out. And we made, back in about 1985 or 6, I can't remember, we had a simple robot doing somersaults to do it in 3D. Really the calculation is the same. You just have to be balancing in the other degrees of freedom. If you're just doing a somersault, it's just a planar thing. Ron Rob was my graduate student and we were at MIT, which is when we made a two legged robot do a 3D somersault for the first time there. In order to get enough rotation rate, you needed to do tucking, also withdraw the legs in order to accelerate it. And, and he did some really fascinating work on how you stabilize more complicated maneuvers. You remember he was a gymnast, a champion gymnast before he'd come to me. So he had the physical abilities and he was an engineer. So he could translate some of that into the math and the algorithms that you need to do that.

He knew how humans do it. You just had to get robots to do the same.

Unfortunately, though, humans don't really know how they do it. Yeah, right. We're coached. We have ways of learning. But do we really understand, in a physics way, what we're doing? Probably most gymnasts and athletes don't know.

So in some way, by building robots, you are, in part, understanding how humans do like walking. Most of us walk without considering how we walk really and how we make it so natural and efficient, all those kinds.

ATLAS still doesn't walk like a person, and it still doesn't walk quite as gracefully as a person, even though it's been getting closer and closer. The running might be close to a human, but the walking is still a challenge.

That's interesting, right, that running is closer to a human. It just shows that the more aggressive and kind of the more you leap into the unknown, the more natural it is. I mean, walking is kind of falling always, right.

And something weird about the knee that you can kind of do this folding and unfolding and get it to work out. Just a human can get it to work out just right. There's compliances, compliance, mainspringiness in the design that are important to how it all works. Well, we used to have a motto at Boston Dynamics in the early days, which was, you have to run before you can walk.

That's a good motto because you also had Wildcat, which was one of the. Along the way towards Spot, which is a quadruped that went 19 miles an hour on flat terrain. Is that the fastest you've ever built?

Oh, yeah.

Might be the fastest quadruped in the world. I don't know.

For a quadruped, probably. Of course, it was probably the loudest, too. So we had this little racing go kart engine on it, and we would get people from three buildings away sending us complaining about how loud it was.

So at the leg lab, I believe most of the robots didn't have knees. How do you figure out what is the right number of actuators? What are the joints to have? What do you need to have? We humans have knees and all kinds of interesting stuff on the feet. The toe is an important part, I guess, for humans, or maybe it's not. I injured my toe recently and it made running very unpleasant. So that seems to be kind of important. So how do you figure out for efficiency, for function, for aesthetics, how many joints to have, how many actuators to have?

Well, it's always a balance between wanting to get where you really want to get and what's practical to do based on your resources or what, you know, and all that. So, I mean, the whole idea of the pogo stick was to do simplification. Obviously, it didn't look like a human. I think a technical scientist could appreciate that we were capturing some of the things that are important in human locomotion without it looking like it, without having a knee, an ankle. I'll tell you, the first sketch that Ben Brown made when we were talking about building this thing was a very complicated thing with zillions of springs, lots of joints. It looked like much more like a kangaroo or an ostrich or something like that. Things we were paying a lot of attention to at the time. So my job was to say, okay, well, let's do something simpler to get started, and maybe we'll get there at some point.

I just love the idea that you two were studying kangaroos and ostriches.

Oh, yeah. We filmed and digitized data from horses. I did a dissection of ostrich at one point, which has absolutely remarkable legs.

Dumb question. Do ostriches have a lot of musculature?