Machine Learning for Autonomous Robot Actions

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Originally Posted by gblake

So... I suggest starting with a simulator.

Yes, that is definitely one of the things I will do. (My team would not take well to being told that our robot was now learning how to play autonomous, and that I had no idea what it would try next!)

This year, I had tried to run a 3 tote automous routine with my team's robot. I had the robot's motion carefully controlled throughout the entire routine, and routines were very repeatable, with very little deviation from run to run. However, I could never seem to get it quite fast enough to complete in time.

We then went to a competition to find another team with a routine almost identical in procedure, but with an extra (almost sloppy) skid here and there, making them fast enough to complete it in time.

My hope is that a machine learning algorithm would be able to optimize autonomous routines to ensure we had the best run possible with a given robot, including finding solutions that a hand-written autonomous may not have. (Including a well-timed skid)

On the other hand, such a system would be very hard to modify mid-competition, and would need a complete re-train in order to, say, drive a little farther into the auto zone.

Oh how I wish for a bigger autonomous mode this coming year....