CPG based Motion Control for Humanoid Locomotion using a Parallel Optimization Method

摘要

In this paper, we propose a motion control method for bipedal humanoid locomotion. The motion control is based on the Central Pattern Generator (CPG), and is optimized by Simulated Annealing. Optimization of parameters in the motion control based on the CPG is very hard problem. The number of the parameters which should be optimized increases as a robot's link structure becomes complicated. To optimize all parameters simultaneously may cause explosion of search space. Therefore, we divide search space into upper-limbs optimization space and leg optimization space. We then propose a parallel optimization method by two processors, which handles the control parameters of upper-limbs and legs, and communicates them each other. In the experiments, our method succeeded in optimization of all parameters without explosion of search space, and performed superior gaits.