University of Bremen

CAPABLE is a capability-aware adaptation framework for frozen vision-language-action policies: a temporal encoder shared across joints infers from command-response history and live Jacobian grounding how much commanded motion each joint still realizes, a self-supervised physical-prediction objective ties that representation to behavior, and a bounded residual reinforcement-learning policy corrects the VLA arm action without fault labels or faulty-joint identifiers; across 28 LIBERO tasks it raises success on an actuator excluded from fault training from 24.8% to 59.3%, 17.4 points above a parameter-matched global-history baseline, while preserving healthy performance.

CAPABLE is a capability-aware adaptation framework for frozen vision-language-action policies: a temporal encoder shared across joints infers from command-response history and live Jacobian grounding how much commanded motion each joint still realizes, a self-supervised physical-prediction objective ties that representation to behavior, and a bounded residual reinforcement-learning policy corrects the VLA arm action without fault labels or faulty-joint identifiers; across 28 LIBERO tasks it raises success on an actuator excluded from fault training from 24.8% to 59.3%, 17.4 points above a parameter-matched global-history baseline, while preserving healthy performance.