RAYA: Learning Where and When to Intervene for Robot Recovery
The paper presents RAYA, a hybrid learned-analytic framework that proactively integrates a learned recoverability margin and an adaptive task scheduler into a robot's controller to enable zero-shot recovery from failures, demonstrating superior survival rates in both extensive simulations and real-world hardware flights compared to existing baselines.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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