I’d like to see us share knowledge about building & training agents for robotics, be they arms, walkers, wheeled, or other.
I’ll start! IRC Freenode ##machinelearning pointed me to this paper in which a joint robot is trained to follow a trajectory with machine learning.
I have a computer simulation of my 6 joint arm. For any given instantaneous pose I can quickly confirm if the pose is legal (not self-colliding). What I don’t have is a good way to avoid singularities over time. For example, as the arm moves near a singularity the elbow has to turn impossibly fast to maintain target speed at the finger tip. I’ve tried to write it many times and there’s always new edge cases I can’t solve. So I’m considering an ML agent to solve the problem for me.
My intuition is that I could set up inputs (start target, end target, interpolation value), output (pose), and using some supervised learning with gradient descent in the simulator to test random movements. For scoring the results I would first test pose/target accuracy, then minimize joint velocity over time. This last bit is the special sauce that (I hope) will encourage the agent to avoid the problem with singularities.
If you can help me make this happen, please comment. I’d love to make it open source and share with everyone.
I’m also interested to read about your adventures in ML, especially quad walkers like Spot Mini clones.