Quote:
Originally Posted by x86_4819
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)
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There is this:
https://github.com/KHEngineering/SmoothPathPlanner
It is designed to be used in real time, but one could compute the velocity time profiles before hand and simply upload them to the robot. Granted this only gets the robot (x,y) (in theory), one still has to do something once it is there, such as pick up a tote or shoot a ball.
Beyond that, you could implement q learning with computer vision (through raw images, or data gathered from vision and sensors) if you have enough computational power. I believe machine learning never will take off unless wireless aerial cameras are allowed.