The Robotic Dexterity Deadlock

I couldn't read it except on archive.org. Here's the link to save people trouble https://web.archive.org/web/20260227201321/https://www.origa...

"This deployment is temporarily paused" is the crappiest "this account has gone over its budget" error page ever. Does that mean the site's down, or is that some meta-joke like "you've reached the end of the Internet"? Quick, explain to my non-technical friends what a "deployment" is. They're not trying to go on a deployment; they're trying to look at a website.

That's a nice piece of motor engineering. It's well known that high ratio gearboxes for robots are a headache. Back driveability doesn't work, and tiny teeth are fragile. Comments on this go all the way back to Feynman writing about his time spent engineering automatic gunnery aiming systems in WWII.

This new discovery is that gearbox problems mess up a machine learning system. It's trying to track gearbox noise and is using up all its learning capacity on that. This discovery means that robotics people can tap machine learning funding for motor and gearbox development. Robotics labs used to be really low-budget operations. No longer.

What you really want is a direct drive motor, but those have to be large-diameter. They can be flat; that's a pancake motor. That's too large for fingers. So their compromise moves partly in that direction; the rotor is flatter, torques are higher, speeds are slower, and gearbox ratios are lower. As they point out, reflected inertia is the square of the gear ratio, because the gear ratio gets you both going out and coming back. So this is a bigger than linear win.

Good back-drivabiilty means much less risk of gear breakage on overload. Some of the academic designs, such as harmonic drives and series elastic actuators, have huge gear ratios in a small space. That's OK for prototypes but not production. As I've mentioned before, "you cannot strip the teeth of a magnetic field", a line from a GE electric locomotive salesman around 1900. If an overload forces a motor backwards, nothing breaks.

Would have been nice to hear more about the motor design. That's the real achievement here. There are CAD tools which understand electromagnetic fields now, so strange motor geometries are not as much of a trial and error and experience process as it once was. It's also respectable for an EE to work on rotating machinery again. That field matured around the 1960s, and until computers took over motor control, didn't change much.

Website down? "This deployment is temporarily paused"

You can redesign every single actuator, sure. Or you can design a wrist camera and use it to close the loop. Or just run enough imitation learning + "RL IRL" and fold the imperfect real world actuators into the policy implicitly.

Robotics doesn't have a single silver bullet - the design space is vast and underexplored.

Nothing scarier than a Vercel bill.

What is the power draw of these joints?

Website is offline, archived snapshot: https://web.archive.org/web/20260227201321/https://www.origa...

It’s not X. It’s Y.

Multiple times, over and over.

We need to stop with the AI stuff.

Surgical robots, and robot pianos both exist. Neither employ humanoid hands. This all just illustrates how humanoid robots are, in multiple dimensions, going down technology rat holes. In some cases better solutions already exist without looking humanoid. In other cases, the humanoid form factor fails to address problems like a high center of gravity in a device that needs to not fall on grandma while helping her around the house.

I continue to be amazed that the wrong form factor keeps being pursued. Though I suppose I shouldn't be too surprised given the parade of failed "AI devices."