Robotic System based on Computational Intelligence – Evolutionary Generation of Regrasping Motion
Toshio Fukuda*, Yasuhisa Hasegawa**
*Center for Cooperative Research in Advanced Science & Technology Nagoya University, Furo-cho 1, Chikusa-ku, Nagoya, 464-8603, Japan
**Department of Micro System Engineering Nagoya University, Furo-cho 1, Chikusa-ku, Nagoya, 464-8603, Japan
The control of multifingered robot hands has been the subject of recent interest. To regrasp an object, there are many parameters to be determined; grasping points, grasping force, regrasping phases, finger allocation and so on. It is difficult to optimize such manipulation parameters for achieving effective manipulation. In this section, we propose generation of regrasping motion for a four-fingered robot hand using Evolutionary Programming (EP). Evolutionary optimization is generally able to find optimal solutions without supervisor after much iteration, which makes it almost impractical to apply a real robot directly. Therefore, we apply the controller in numerical simulation to the real robot hand. We show effectiveness of the propose method for the regrasping motion with experimental results.