GRASP: Gradient-Guided Sampling for Contact-Rich Physics-Based Motion Retargeting
We study physics-based retargeting of human demonstrations for robot learning: finding robot controls that reproduce reference motions under contact dynamics. We propose GRASP (Gradient Recovery from Archived Samples for Proposals), which combines sampling-based exploration with gradient-guided refinement without requi...