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WRAP achieves a 27.4% reduction in localization error by decoupling mean adaptation from covariance robustification, revolutionizing how we approach robot localization under variable conditions.
AutoSafe enables seamless integration of safety and performance in online reinforcement learning, achieving robust safety without sacrificing learning smoothness.
