A human-like real-time grasp synthesis method for humanoid robot hands

Abstract

This paper addresses a real-time grasp synthesis of multi-fingered robot hands to find grasp configurations which satisfy the force closure condition of arbitrary shaped objects. We propose a fast and efficient grasp synthesis algorithm for planar polygonal objects, which yields the contact locations on a given polygonal object to obtain a force closure grasp by a multi-fingered robot hand. For an optimum grasp and real-time computation, we develop the preference and the hibernation process and assign the physical constraints of a humanoid hand to the motion of each finger. The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics of human grasping. The proposed method reduces the computational time significantly at the sacrifice of global optimality, and enables grasp posture to be changeable within 2-finger and 3-finger grasp. The performance of the presented algorithm is evaluated via simulation studies to obtain the force-closure grasps of polygonal objects with fingertip grasps. The architecture suggested is verified through experimental implementation to our developed robot hand system by solving 2- or 3-finger grasp synthesis.