Performance Evaluation Of Biped Robot Optimal Gait Based On Genetic Algorithm

Abstract

A Genetic Algorithm (GA) gait synthesis method for walking biped robots is considered in this paper. The walking occupy most of the time during the task performance, therefore its gait is analyzed based on the minimum consumed energy (CE) and minimum torque change (TC). The biped robot optimal gait is considered starting from static standing state and continuing with normal walking. The proposed method can be applied for wide ranges of step lengths and step times and for other tasks that might to be performed by humanoid robot. By using GA as an optimization tool it is easy to include constraints and add new variables to be optimized. The biped robot gait is generated without neglecting the stability, which is verified by the zero moment point ZMP concept. Simulations are realized based on the parameters of "Bonten-Maru I" humanoid robot. The evaluation by simulations shows that the proposed method has a good performance and energy is significantly reduced.