Generation of Regrasping Motion for Multi-Fingered Robot Hand by Evolutionary Programming

Abstract

The control of multi-fingered robot hands has been the subject of recent interest. To manipulate some object with rerasping motion, there are many parameters to be determined ; the grasping points, grasping forces, regrasping phases, finger allocation and so on. It is difficult to optimize such manipulation parameters for achieving effective manipulation. In this paper, we propose a generation algorithm of regrasping motion for a four-fingered robot hand using Evolutionary Programming (EP). Evolutionary optimization method is generally able to find optimal solutions without supervisor after much iteration, which makes it almost impractical to apply a real robot in online learning process. Therefore we apply the controller generated in numerical simulations to the real robot hand. We show effectiveness of the proposed generation algorithm for the regrasping motion with experimental results.