2026
Toward a Multi-Embodied Grasping Agent
RA-L 2026
Multi-embodiment grasping aims to develop approaches that exhibit generalist behavior across diverse gripper designs. Existing methods often learn the gripper kinematic structure implicitly and face challenges due to the difficulty of sourcing the required large-scale data. In this work, we present