[Climato]

I think about this regularly just don't have the time to pursue it:

Couldn't you build your arm in Nvidia Omniverse by also adding feedback like a cheap hig resolution distance or angle detector and train an ml model to compensate it?

[GabeIsko]

Making and animating a 3D graphics robot arm is trivial compared to building it in real life. So not so much Omniverse, you would want to use a proper simulator like gazebo.

But beyond that, the kinematics as well as the force dynamics for controlling a serial manipulator are very well understood. So there aren't too many gains to be made by AI. It is difficult to implement in software due to some tricky situations about the nature of motion planning. Discontinuities around orientation approaches in 6-DOF systems for instance. But widespread use of serial manipulators is proof that, although challenging, they are relatively solved. It is always interesting to watch an AI model or genetic algorithm do some path planning, but this is a pretty well trod area of research at this point.

Now, when you want a robot to walk and pick things up at the same time... that is when AI becomes something to consider in order to figure out how the dynamics should work.

[app13]

Omniverse is a simulation platform specifically designed to do things like train/test robotics. It's not a creative engine like UE or Unity.

[GabeIsko]

I'm not super familiar, but they say in the webpage that it is specifically for Universal Scene Description, which is formally for graphics. Although, after a quick google, it looks like they do have a simulation package which then runs on top of Omniverse (Isaac Sim?), so I guess that is Nvidia's robotics offering.

My general experience with other commercial offerings for simulation... is not great. In my experience, people usually end up migrating to gazebo, but I have been away from the field for a while now so it could be different. It is probably a situation where Nvidia will have a few coporate clients that they prioritize, and you are on your own to get it set up if you aren't on that lists. Pretty normal.

[Climato]

I meant to control single segments to compensate for build quality.

1 AI model per motor

[GabeIsko]

But motor and motion control isn't exactly so mysterious that we need AI for it. Inductance in electric motors can have some odd effects in the acceleration domain, but it generally boils down to a second to third order differential formula. Even when linking multiple together in a serial manipulator, the math is really well understood for modeling the motion output. Maybe there are some outputs to be gained implementing different drive trains in arbitrary circumstances, and monitoring how they fail and stuff like that. At that point you are really getting into the weeds of operations and maintenance more than actual motion control.

The situation that arises into a very complex n-dimensional problem that you would want AI to search through is the coordinated motion of multiple actuators to achieve a very complex output. Like, picking something up of unknown weight, running while carrying it up a steep hill, waving it around while doing all this. We take it for granted as humans with brains that can perform all this stuff trivially, but it is extremely complex motion.

[Climato]

The problem this ml should solve is pricing: get cheaper components and compensate with ml.

Basically increasing the precision of the arm by controlling the voltage much more precisely

[GabeIsko]

Well, that doesn't really work. There is only so much electrical efficiency you can crank out of these motor. Essentially, there is a relationship between the current you pump through them, which is limited by their thermal characteristics, and the inductance of them. So you are trading off building more inductive motors that are more powerful but less reactive, and current draw which you can increase by putting more material in the motor and making it dispose heat much better but also bulkier. There are diminishing returns in many places in this process, and at a certain point you have to consider switching to hydraulics if you more force at a high reactivity, under essentially much less energy efficient conditions.

Maybe you could make a model that sizes motors correctly per application? But you are still much better hiring an engineer that knows what they are doing that can explain what is going on and trouble shoot things when they go wrong. At a certain point you are trying to figure out how to completely replace an engineer with a machine learning model, which I would like to think is a bad idea.