It’s actually going faster because it does not require public approval the same way that driving cars do because you’re in public space.

We’re seeing a lot of robotic trials happening in private warehouses and on private test ranges at pretty rapid scale

Beyond that the methods for transfer learning behavior cloning behavior authoring are very robust so that I can get joint angles directly from a human via instrumentation through vision or even commodity sensors which captured trajectories that can be immediately applied to robotic joint positions.

The real challenge is actually capturing demonstration recordings from humans because it’s the hardest thing to instrument. The core task is instrumenting data capture of existing human tasks that are not done through machines, such that they can transfer to machines.

This is easiest done with existing human operated robots because the instrumentation is free, so data can go directly into real2sim2real pipelines.

There might seem counterintuitive but most of the actual technical bits and bites are already there it’s re-orienting the economic and logistical process of labor execution that is the major challenge.

I will say though, I’m seeing less and less barriers there as time goes on. Employers really want to not have to hand human employees

Municipal approval was probably only a minor part of the development time tho no? Google was operating Waymo in Mountain View for years before they expanded. The vast majority of the time cost was in development.

I think technology development can be faster thanks to better AI systems like VLA models, but I do think the time to real deployment will be long.

My pet issue is that the dexterity of the hands is still really poor. A human hand is incredible with what it can do.

I think between the general manipulation tasks, world understanding, and more these systems are still a long ways out for widespread use, though I wouldn’t be surprised if they find niche uses near term.