Tumbling robots are simple platforms that are able to traverse large obstacles relative to their size, at the cost of being difficult to control. Existing control methods apply only a subset of possible robot motions and make the assumption of flat terrain. Reinforcement learning (RL) allows for the development of sophisticated control schemes that can adapt to diverse … [Read more...] about Tumbling Robot Control Using Reinforcement Learning: An Adaptive Control Policy That Transfers Well to the Real World
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