Embedded generalizations?
'Fake' Data Helps Robots Learn the Ropes Faster
University of Michigan News, June 29, 2022
University of Michigan (U-M) researchers expanded training datasets for teaching robots to work with soft objects like ropes and fabrics, to expedite the learning process. U-M's Dmitry Berenson and Peter Mitrano augmented an optimization algorithm to enable a computer to make human-level generalizations, forecasting how dynamics observed in one case might recur in others and generating variants of the first experiment's result that serve the robot in the same way. In simulations, the expanded dataset improved the success rate of a robot looping a rope around an engine block by 48%, which increased to 70% after training. An experiment using a physical robot to perform the same task almost doubled its success rate over the course of 30 tries. ....
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