GOAG: Generative and Object-Agnostic Grasp Planner for Dexterous Robotic Manipulation
Research
Source: arXiv cs.ROPublish time unverified
arXiv:2608.19759v1 Announce Type: new Abstract: Multifingered grasping is a crucial robotic skill, but current deep-learning grasp planners often struggle to generalize to new objects because they are trained on limited, object-specific datasets. We introduce a fundamentally different approach, grounded in the observation that the gripper and the object share identical surface geometry at their mutual contact points.