2023
Sampling-based Exploration for Reinforcement Learning of Dexterous Manipulation
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In this paper, we present a novel method for achieving dexterous manipulation of complex objects, while simultaneously securing the object without the use of passive support surfaces. We posit that a key difficulty for training such policies in a Reinforcement Learning framework is the difficulty of…