Abstract
In this paper, we study inverse kinematics problems in which the trajectories of walking robot toes are generated under the condition of minimum walking energy. It is important for a walking robot that motions of legs are determined to achieve a desired body motion. A 4-legged walking robot with two rinks and two motors at joints of waist and knee is assumed in this study. A mathematical optimization method is used for the optimization of several parameters which describe the trajectory function of toe. A fuzzy clustering is applied to select teaching data for neural networks to obtain trajectory parameters. Some trained neural network controllers are applied to each obstacle by switching over.
