Simulation enables engineers to prototype rapidly and with minimal human effort. In robotics, physics simulations provide a secure and low-cost virtual playground for robots to gain physical skills through Deep Reinforcement Learning (DRL). However, simulations use hand-derived physics that will have difficulty adapting when tested on real hardware. This challenge is termed the “sim-to-real gap”…

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