UniIntervene uses future-conditioned action-value estimation and a temporal value-risk critic to trigger memory-based recovery interventions, reporting 8.6% higher success rates and 57% fewer human interventions than prior HiL-RL methods on real manipulation tasks.
Empowering embodied manip- ulation: A bimanual-mobile robot manipulation dataset for household tasks
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RoboMIND is a large-scale multi-embodiment teleoperation dataset for robot manipulation containing 107k trajectories across four robots, with failure annotations and a digital twin simulator.
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RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation
RoboMIND is a large-scale multi-embodiment teleoperation dataset for robot manipulation containing 107k trajectories across four robots, with failure annotations and a digital twin simulator.