Robert Playter

Well, again, this stuff has really evolved rapidly in the last few years.

The first time we did a somersault, there was a lot of kind of manual iteration.

What is the trajectory?

You know, how hard do you throw?

In fact, in these early days, I actually would, when I'd see early experiments that the team was doing, I might make suggestions about how to change the technique.

Again, kind of borrowing from my own intuition about how backflips work.

But frankly, they don't need that anymore.

So in the early days, you had to iterate kind of in almost a manual way, trying to change these trajectories of the arms or the legs to try to get a successful backflip to happen.

But more recently, we're running these model predictive control techniques where we're able to, the robot essentially can think in advance for the next second or two about how its motion is going to transpire.

And you can solve for optimal trajectories to get from A to B. So this is happening in a much more natural way.

And we're really seeing an acceleration happen in the development of these behaviors

Again, partly due to these optimization techniques, sometimes learning techniques.

So it's hard in that there's a lot of mathematics behind it.

But we're figuring that out.

But that's the cool part, right?

So, you know.

Yeah.

You know, the physics, we can calculate physics pretty well using Newton's laws about how it's going to evolve over time.

The sick trick, which was a front somersault with a half twist is a good example, right?

You saw the robot on various versions of that trick.