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Learning policies in simulation and transferring them to the real world has become a promising approach in dexterous manipulation.
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A. Gupta, J. Yu, T. Z. Zhao, V. Kumar, A. Rovinsky, K. Xu, T. Devlin, and S. Levine, “Reset-free reinforcement learning via multi-task learning: Learning dexterous manipulation behaviors without human intervention,” in ICRA , 2021
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