PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers
Michael Xu, Yi Shi, KangKang Yin, Xue Bin Peng
Abstract
physics-based tracking controller to imitate the motions in simulation.The corrected motions are then added to the dataset, which is used to continue training the motion generator in the next iteration.PARC's iterative process jointly expands the capabilities of the motion generator and tracker, creating agile and versatile models for interacting with complex environments.PARC provides an effective approach to develop controllers for agile terrain traversal, which bridges the gap between the scarcity of motion data and the need for versatile character controllers.
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Install the CLIlune papers fulltext 37c8a262-9aca-4d0d-9fa0-2e2c1d4cfd22Cited by top-tier papers7
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