Manipulation

Regrasping

Regrasping is the deliberate change of a robot's grasp on an object, either by placing the object down and picking it up differently, transferring it between two hands or arms, or manipulating it within the hand. It is required when the initial feasible grasp is incompatible with the downstream task, such as inserting a part that was grasped over its mating surface, and it is a classic planning problem combining grasp and placement reasoning.

Why it matters for physical AI

Regrasp competence separates single-shot pick-and-place from genuine task versatility, and dual-arm handovers and in-hand regrasps are increasingly prominent skills in bimanual learning benchmarks.