A biped humanoid robot's gait planning method based on Artificial Immune Network

Abstract

A biped humanoid robot model with 12 degree of freedom is developed in this paper. To facilitate the gait pattern planning, the 3D inverted pendulum model and the ZMP are introduced to enable a human-like stable walking. Since the searching of best walk primitive is a multi-objective optimization problem, a modified aiNet Algorithm as well as SGA Algorithm is applied to the optimization process. Finally, the control parameters worked out by both algorithms are verified and compared in simulation. We find out that the result of aiNet provides the robot with better stability than SGA while they are similar in mobility.