RESETTLE: Robotic Recovery through Disagreement-Triggered Retrieval and Efficient Corrective Control
RESETTLE is a model-agnostic framework for recovering frozen robot policies when two independent action proposals disagree persistently. It triggers recovery by retrieving a successful demonstration, and executes one corrective action using state-servo control refined by a visual residual. This method improves task success rates with low computational overhead, allowing local correction without retraining or complex online planning.