Regrasping behavior generation for rectangular solid object

Abstract

The control of multi-fingered robot hands has been the subject of interest. To manipulate some object with regrasping 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. We propose a generation method of regrasping motion for a four-fingered robot hand using evolutionary programming (EP). In this case, EP determines not only finger motions, but also rotation of the target object in order to increase its manipulability. In manipulating an object like a rectangular solid, it is very important to change the object directions and to grasp another face according to the task progress because the grasping faces tend to be limited to only two. The evolutionary optimization method is generally able to find optimal solutions without a supervisor after much iteration, which makes it almost impractical to apply a real robot directly. Therefore we control the real robot hand with an optimal controller that has been generated in computer simulations. We show the effectiveness of the proposed acquisition method for the regrasping motion with experimental results.