GUARD: Anomaly-Informed Q-Steering for Generative Robot Policies in Dexterous Manipulation
Overview
This research presents GUARD, a framework that leverages anomaly scores derived from training data to guide generative robot policies during execution.
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- arXiv Robotics — research abstractsSignalGUARD: Anomaly-Informed Q-Steering for Generative Robot Policies in Dexterous Manipulation
This research presents GUARD, a framework that leverages anomaly scores derived from training data to guide generative robot policies during execution.
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