A GA BASED BIPED ROBOT GAIT OPTIMIZATION FOR GOING UP-STAIRS AND A NN IMPLEMENTATION

摘要

In this paper, a Genetic Algorithm (GA) gait synthesis method is proposed, which generates the angle trajectories of biped robot for going up-stairs based on the minimum consumed energy and minimum torque change. The proposed method can be applied for a wide range of step lengths, stair heights and step times. The angle trajectories are generated without neglecting the stability of the biped robot. In order to verify the effectiveness of the proposed method, the results for minimum consumed energy and minimum torque change are compared. A Radial Basis Function Neural Network (RBFNN) is considered for the real time application. Simulations are realized based on the parameters of the "Bonten-Maru I" humanoid robot. The evaluation by simulations shows that the proposed method has a good performance.