Brett Adcock

Our whole controller, so we have a main computer, is processing what to tell all the joints to do 200, maybe more than 200 times a second to make sure we can just balance.

And then we can do the task.

It could be reaching over and grabbing this or balancing.

If we run that too slow, we just don't have enough feedback.

and we just fall over, just like, yeah, we have to fully balance.

You know, it's dynamic.

So it's, if you, generally, if you power it off mid-run, it's going to just fall down.

It's not like a four-legged dog or quadruped robot where, like, at any given point, it's usually statically stable.

So it makes it very difficult because you have to be able to even move your hand.

I'm moving my pelvis and my whole body, my torso's moving, my head's moving.

Like, all of it becomes very complicated now.

It's not just, like, move my hand.

It's, like, move my whole body to get my hand in the right spot.

So every joint, all those 40 joints have basically position encoders.

So we know exactly what position the motor's at, or even the case of the knee or this.

And we have force sensing, torque sensing on board.

We have the ability to detect all the forces that that knee is seeing.

It could be really high when it's walking, or it could be like, you know, it could be like, it could be powered off and have no forces on the leg.

all of that feedback and is being sent in the main computer.

And then we're telling all the joints what to do over 200 times a second.