Grasp Synthesis in Cluttered Environments for Dexterous Hands

Abstract

We present an algorithm for efficiently generating collision-free force-closure grasps for dexterous hands in cluttered environments. Computing a grasp is complicated by the high dimensionality of the hand configuration space, and the high cost of validating a candidate grasp by collision-checking and testing for force-closure. When an object is placed in a new scene, we use a novel cost function to focus our search to good regions of hand pose space for a given preshape. The proposed cost function is fast to compute and encapsulates aspects of the object, the scene, and the force-closure of the ensuing grasp. The low-cost candidate grasps produced by the search are then validated. We demonstrate the generality of our approach by testing on the 3-fingered 4DOF Barrett hand and the anthropomorphic 22DOF Shadow hand. We also propose an extension of the algorithm for two-handed grasps and demonstrate it on the HRP3 hands. Our results show that the candidate grasps generated by our algorithm consistently have high probability of being valid for various hands, objects and scenes. Finally, we describe an implementation on a WAM arm with a Barrett Hand.