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This work proposes CARE (Corrective Atomic Robotic Execution), a framework that improves recovery by learning from failures encountered during execution, and introduces the Failure State Recovery Benchmark (FSR-Bench), which evaluates recovery from intermediate failure states under local deviations and structural anomalies.
The results show that a diffusion policy can benefit substantially from knowing where an interaction is heading, without being told exactly where to move.
