Robert Playter is CEO of Boston Dynamics, a legendary robotics company that over 30 years has created some of the most elegant, dextrous, and simply amazing robots ever built, including the humanoid robot Atlas and the robot dog Spot. Please support this podcast by checking out our sponsors:
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OUTLINE:
0:00 - Introduction
2:57 - Early days of Boston Dynamics
11:18 - Simplifying robots
15:16 - Art and science of robotics
19:59 - Atlas humanoid robot
36:53 - DARPA Robotics Challenge
51:13 - BigDog robot
1:05:02 - Spot robot
1:26:27 - Stretch robot
1:29:15 - Handle robot
1:34:49 - Robots in our homes
1:43:36 - Tesla Optimus robot
1:52:18 - ChatGPT
1:55:22 - Boston Dynamics AI Institute
1:56:53 - Fear of robots
2:07:16 - Running a company
2:12:52 - Consciousness
2:20:26 - Advice for young people
2:22:21 - Future of robots

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And so our goal was a natural looking gate.

It was surprisingly hard to get that to work.

It was the prototype before the Petman robot.

And it had a really nice looking gate where, you know, it would stick the leg out, it would do heel strike first before it rolled onto the toes.

You didn't land with a flat foot, you extended your leg a little bit.

But even then it was hard to get the robot to walk when you're walking, that it fully extended its leg.

And getting that all to work well took such a long time.

In fact, I probably didn't really see the nice natural walking that I expected out of our humanoids until maybe last year.

And the team was developing on our newer generation of Atlas, you know, some new techniques for developing a walking control algorithm.

And they got that natural looking motion as sort of a byproduct of just a different process they were applying to developing the control.

So that probably took 15 years, 10 to 15 years to sort of get that from, you know, the Pet Man prototype was probably in 2008 and what was it, 2022.

Last year though, I think I saw a good walking on Atlas.

The following is a conversation with Robert Plater, CEO of Boston Dynamics, a legendary robotics company that over 30 years has created some of the most elegant, dexterous, and simply amazing robots ever built, including the Humanoid Robot Atlas and the robot dog Spot, 1 or both of whom you've probably seen on the internet, either dancing, doing backflips, opening doors, or throwing around heavy objects.

Robert has led both the development of Boston Dynamics humanoid robots and their physics-based simulation software.

He has been with the company from the very beginning, including its roots at MIT, where he received his PhD in aeronautical engineering.

This was in 1994 at the legendary MIT Leg Lab.

He wrote his PhD thesis on robot gymnastics, as part of which he programmed a bipedal robot to do the world's first 3D robotic somersault.

Robert is a great engineer, roboticist and leader and Boston Dynamics to me as a roboticist is a truly inspiring company.

This conversation was a big honor and pleasure and I hope to do a lot of great work with these robots in the years to come.

To support it, please check out our sponsors in the description.

And now, dear friends, here's Robert Blader.

When did you first fall in love with robotics?

Well, love is relevant because I think the fascination, the deep fascination is really about movement.

And I was visiting MIT looking for a place to get a PhD.

And 1 of my professors in the aero department said, go see this guy Mark Raber down in the basement of the AI lab.

He showed me his robots and he showed me this robot doing a somersault.

And I just immediately went, whoa, you know, robots can do that.

And because of my own interest in, in gymnastics, there was like this immediate connection.

And, you know, I was interested in, I was in a aero-astro degree because flight and movement was all so fascinating to me.

And then it turned out that robotics had this big challenge.

How do you build a legged robot that can really get around?

They're still working on perfecting motion in robots.

What about the elegance and the beauty of the movement itself?

Is there something maybe grounded in your appreciation of movement from your gymnastics days?

Was there something you just fundamentally appreciated about the elegance and beauty of movement?

You know, we had this concept in gymnastics of letting your body do what it wanted to do when you get really good at gymnastics.

Part of what you're doing is putting your body into a position where the physics and the body's inertia and momentum will kind of push you in the right direction in a very natural and organic way.

And the thing that Mark was doing, you know, in the basement of that laboratory was trying to figure out how to build machines to take advantage of those ideas.

How do you build something so that the physics of the machine just kind of inherently wants to do what it wants to do?

And he was building these springy pogo stick type, you know, his first cut at Legged Locomotion was a pogo stick where it's bouncing and there's a spring mass system that's oscillating, has its own sort of natural frequency there.

And sort of figuring out how to augment those natural physics with also intent, how do you then control that but not overpower it?

It's that coordination that I think creates real potential.

We could call it beauty, you could call it, I don't know, synergy.

But I think that that was inherent from the beginning that was clear to me that that's part of what Mark was trying to do.

He asked me to do that in my research work, so that's where it got going.

So part of the thing that I think I'm calling elegance and beauty in this case, which was there, even with the Pogo stick, is maybe the efficiency, so letting the body do what it wants to do, trying to discover the efficient movement.

It also becomes easier to control in its own way because the physics are solving some of the problem itself.

It's not like you have to do all this calculation and overpower the physics.

The physics naturally, inherently want to do the right thing.

There can even be, you know, feedback mechanisms, stabilizing mechanisms that occur simply by virtue of the physics of the body.

And it's not all on the computer or not even all in your mind as a person.

And there's something interesting in that melding.

You were with Mark for many, many, many years.

You were there in this kind of legendary space of Leg Lab at MIT in the basement.

Is there some memories from that time that you have?

Because it's such cutting edge work in robotics and artificial intelligence.

The memories, the distinctive lessons, I would say, I learned in that time period, and that I think Mark was a great teacher of, was it's okay to pursue your interests, your curiosity.

You'll do it a lot better if you love it.

That is a lasting lesson that I think we apply at the company still, and really is a core value.

So the interesting thing is I get to, With people like Russ Tedrick and others, like the students that work at those robotics labs are like some of the happiest people I've ever met.

A lot of them are kind of broken by the wear and tear of the process.

But roboticists are, while they work extremely hard and work long hours, there's a happiness there.

The only other group of people I've met like that are people that skydive a lot.

For some reason, there's a deep, fulfilling happiness.

Maybe from a long period of struggle to get a thing to work and it works and there's a magic to it, I don't know exactly.

Because it's so fundamentally hands on and you're bringing a thing to life.

I don't know what it is, but they're happy.

We see, you know, our attrition at the company is really low.

And I think part of that is that there's perhaps a natural connection to it.

It's a little bit easier to connect when you have a robot that's moving around in the world, and part of your goal is to make it move around in the world.

And this is 1 of the unique things about the kinds of robots we're building is this physical interaction lets you perhaps identify with it.

So I think that is a source of happiness.

I think anybody also who is just pursuing something they love, it's easier to work hard at it and be good at it.

And I think we're lucky as an organization that we've been able to build a business around this and that keeps people engaged.

So if it's all right, let's linger on Mark for a little bit longer, Mark Raybert.

He's a legendary engineer and roboticist.

What have you learned about life about robotics from Mark?

Through all the many years you worked with him?

I think the most important lesson, which was, you know, have the courage of your convictions and do what you think is interesting.

Be willing to try to find big, big problems to go after.

And at the time, you know, Like at Locomotion, especially in a dynamic machine, nobody had solved it, and that felt like a multi-decade problem to go after.

And so, you know, have the courage to go after that, because you're interested.

So that's really probably the most important lesson I think that I got from Mark.

How crazy is the effort of doing legged robotics at that time especially?

You know, Mark got some stuff to work starting from the simple ideas.

So maybe the other, another important idea that has really become a value of the company is try to simplify a thing to the core essence.

And while Mark was showing videos of animals running across the savanna or climbing mountains, what he started with was a pogo stick because he was trying to reduce the problem to something that was manageable and getting the pogo stick to balance had in it the fundamental problems that if we solved those you could eventually extrapolate to something that galloped like a horse.

And so look for those simplifying principles.

How tough is the job of simplifying a robot?

So I'd say in the early days, the thing that made Boston, the researchers at Boston Dynamics special is that we worked on figuring out what that central principle was, and then building software or machines around that principle.

And It took real expertise in understanding the dynamics of motion and feedback control principles.

How to build, with computers at the time, how to build a feedback control algorithm that was simple enough that it could run in real time at a thousand hertz and actually get that machine to work.

That was not something everybody was doing at that time.

I think the approaches to controlling robots are going to change, and they're going to become more broadly available.

But at the time, there weren't many groups who could really work at that principled level with both the software and make the hardware work.

And I'll say 1 other thing about you were sort of talking about what are the special things.

The other thing was, it's good to break stuff.

Use the robots, break them, repair them, you know, fix and repeat, test, fix and repeat.

And that, and that's also a core principle that has become part of the company.

And it lets you be fearless in your work.

Too often if you are working with a very expensive robot, maybe 1 that you bought from somebody else or that you don't know how to fix, then you treat it with kit gloves and you can't actually make progress.

And so I think that's been a principle as well.

So just to linger on that psychologically, how do you deal with that?

Because I remember I had, I built a RC car that had some, it had some custom stuff like compute on it and all that kind of stuff, cameras.

And because I didn't sleep much, the code I wrote had an issue where it didn't stop the car and the car got confused and at full speed at like 20, 25 miles an hour slammed into a wall.

And I just remember sitting there alone in a deep sadness.

Sort of full of regret, I think, almost anger, but also like sadness because you think about, well, these robots, especially for autonomous vehicles, like you should be taking safety very seriously even in these kinds of things.

It made me more afraid probably to do this kind of experiments in the future.

Perhaps the right way to have seen that is positively.

It depends if you could have built that car or just gotten another 1, right?

I remember when I got to grad school, you know, I got some training about operating a lathe and a mill up in the machine shop, and I could start to make my own parts.

And I remember breaking some piece of equipment in the lab and then realizing, because maybe this was a unique part and I couldn't go buy it.

And I realized, oh, I can just go make it.

It might take more work than you thought it was gonna be required to get this thing done, but you can just go make it.

And that's freeing in a way that Nothing else is.

You mentioned the feedback control, the dynamics.

Sorry for the romantic question, but in the early days and even now, is the dynamics probably more appropriate for the early days?

And trying to develop scientific principles that let you extrapolate from one-legged machine to another, develop a core set of principles like a spring mass bouncing system, and then figure out how to apply that from a one-legged machine to a 2 or a four-legged machine.

Those principles are really important, and were definitely a core part of our work.

There's also, you know, when we started to pursue humanoid robots, there was so much complexity in that machine that, You know, 1 of the benefits of the humanoid form is you have some intuition about how it should look while it's moving.

And that's a little bit of an art, I think.

Now it's a—or maybe it's just tapping into a knowledge that you have deep in your body and then trying to express that in the machine.

But that's an intuition that's a little bit more on the art side.

You know, before you have the knowledge of how to control it, you try to work through the art channel.

And humanoids sort of make that available to you.

If it had been a different shape, maybe you wouldn't have had the same intuition about it.

Yeah, so your knowledge about moving through the world is not made explicit to you.

might be hard to actually articulate exactly.

There's something about, and being a competitive athlete, there's something about seeing movement.

A coach, 1 of the greatest strengths a coach has is being able to see some little change in what the athlete is doing and then being able to articulate that to the athlete.

And then maybe even trying to say, and you should try to feel this.

And again, sometimes it's hard to articulate what it is you're seeing.

But there's a, just perceiving the motion at a rate that is, again, sometimes hard to put into words.

Yeah, I wonder how it is possible to achieve truly elegant movement.

You have a movie like Ex Machina, not sure if you've seen it, but the main actress in that, who plays the AI robot, I think is a ballerina.

I mean, just the natural elegance and the, I don't know, eloquence of movement.

It looks efficient and easy and just, it looks right.

And then you look at, especially early robots, I mean, they're so cautious in the way they move that it's not the caution that looks wrong, it's something about the movement that looks wrong that feels like it's very inefficient, unnecessarily so.

And it's hard to put that into words exactly.

We think, and part of the reason why people are attracted to the machines we build is because the inherent dynamics of movement are closer to right.

Because we try to use walking gates or we build a machine around this gate where you're trying to work with the dynamics of the machine instead of to stop them.

You know, Some of the early walking machines, you're essentially, you're really trying hard to not let them fall over, and so you're always stopping the tipping motion.

And sort of the insight of dynamic stability in a lugged machine is to go with it.

Let the tipping happen, let yourself fall, but then catch your catch yourself with that next foot.

And there's something about getting those physics to be expressed in the machine that people interpret as lifelike, or, or elegant, or just natural looking.

And so I think if you get the physics right, it also ends up being more efficient, likely.

There's a benefit that it probably ends up being more stable in the long run.

You know, it could walk stably over a wider range of conditions.

And it's more beautiful and attractive at the same time.

So how hard is it to get the humanoid robot Atlas to do some of the things it's recently been doing.

Maybe you can correct me, but there's something about running.

Our first humanoid, we needed to deliver natural looking walking.

You know, we took a contract from the army, they wanted a robot that could walk naturally, they wanted to put a suit on the robot and be able to test it in a gas environment.

And so they wanted the motion to be natural.

And it had a really nice looking gate where it would stick the leg out, it would do heel strike first before it rolled onto the toes.

So you didn't land with a flat foot, you extended your leg a little bit.

But even then it was hard to get the robot to walk where when you were walking that it fully extended its leg and essentially landed on an extended leg.

And if you watch closely how you walk, you probably land on an extended leg, but then you immediately flex your knee as you start to make that contact.

So that probably took 15 years, 10 to 15 years to sort of get that from, you know, the Pet Man prototype was probably in 2008, and what was it, 2022.

Last year, though, I think I saw good walking on Atlas.

If you could just like linger on it, what are some challenges of getting good walking?

So is it, is this partially like a hardware, like actuator problem?

Is it the artistic element of just observing the whole system operating in different conditions together.

I mean, is there some kind of interesting quirks or challenges you can speak to, like the heel strike or

Yeah, so 1 of the things that makes like this straight leg a challenge is you're sort of up against a singularity, a mathematical singularity, where when your leg is fully extended, it can't go further the other direction, right?

There's only, you can only move in 1 direction.

And that makes all of the calculations around how to produce torques at that joint or positions makes it more complicated.

And so having all of the mathematics so it can deal with these singular configurations is 1 of many challenges that we face.

And I'd say in those earlier days, again, we were working with these really simplified models.

So we're trying to boil all the physics of the complex human body into a simpler subsystem that we can more easily describe in mathematics.

And sometimes those simpler subsystems don't have all of that complexity of the straight leg built into them.

And so What's happened more recently is we're able to apply techniques that let us take the full physics of the robot into account and deal with some of those strange situations like the straight leg.

So is there a fundamental challenge here that it's, maybe you can correct me, but is it under-actuated?

You can't push the robot in any direction you want to, right, and so that is 1 of the hard problems of light-gated locomotion.

you have to do that for natural movement.

It's not necessarily required for natural movement.

It's just required, you know, we don't have a gravity force that you can hook yourself onto to apply an external force in the direction you want at all times, right?

The only external forces are being mediated through your feet and how they get mediated depend on how you place your feet and you know, you can't just you know, God's hand can't reach down and give and push in any direction you want.

Is there some extra challenge to the fact that Alice is such a big robot?

The humanoid form is attractive in many ways, but It's also a challenge in many ways.

You have this big upper body that has a lot of mass and inertia.

And throwing that inertia around increases the complexity of maintaining balance.

And as soon as you pick up something heavy in your arms, you've made that problem even harder.

And so in the early work in the leg lab and in the early days at the company, we were pursuing these quadruped robots, which had a kind of built-in simplification.

You had this big rigid body and then really light legs.

So when you swing the legs, the leg motion didn't impact the body motion very much.

All the mass and inertia was in the body.

But when you have the humanoid, that doesn't work.

You have big heavy legs, You swing the legs, it affects everything else.

And so, dealing with all of that interaction does make the humanoid a much more complicated platform.

And I also saw that, at least recently, you've been doing more explicit modeling of the stuff you pick up.

So you have to, what, model the shape, the weight distribution, I don't know, like you have to include that as part of the modeling, as part of the planning.

Because, okay, so for people who don't know, so Atlas, at least in a recent video, throws a heavy bag, throws a bunch of stuff.

So what's involved in picking up a thing a heavy thing and when that thing is a bunch of different non-standard things, I think it also picked up like a barbell and To be able to throw in some cases.

What are some interesting challenges there?

So we were definitely trying to show that the robot and the techniques we're applying to Atlas let us deal with heavy things in the world.

Because if the robot's gonna be useful, it's actually gotta move stuff around.

That's an appreciable portion of the body weight of the robot.

And we also think this differentiates us from the other humanoid robot activities that you're seeing out there.

But just like you or me, you need to anticipate that moment.

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Robert Playter: Boston Dynamics CEO on Humanoid and Legged Robotics | Lex Fridman Podcast #374