ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulation

arXiv:2309.03891v2 Announce Type: replace-cross
Abstract: We present ArtiGrasp, a novel method to synthesize bi-manual hand-object interactions that include grasping and articulation. This task is challenging due to the diversity of the global wrist motions and the precise finger control that are necessary to articulate objects. ArtiGrasp leverages reinforcement learning and physics simulations to train a policy that controls the global and local hand pose. Our framework unifies grasping and articulation within a single policy guided by a single hand pose …

abstract arxiv control cs.cv cs.lg cs.ro diversity global grasping interactions novel objects reinforcement reinforcement learning synthesis type