Learning Quality-Controllable Robot Policies with Iterative Hindsight Relabeling
Quality-Controllable Policy is introduced, a robot policy that enables inference-time control over both individual quality attributes and their combinations and their combinations, and an iterative hindsight relabeling loop is proposed to extend the controllable quality range beyond initial demonstrations.