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This work proposes residual reinforcement learning as an implicit safety-filtering mechanism for safe humanoid control and shows that the residual policy can act as an implicit safety filter.
Escape stochastic robotic systems' safety limitations with EigenSafe, a spectral method that learns a safety filter from the dominant eigenpair of a dynamic programming operator.
