The stability study of biped robot based on GA and neural network

Authors:
Lun Xie;Zhiliang Wang;Kun Wu
Affiliations:
School of Information Engineering, University of Science and Technology Beijing, Beijing, China;School of Information Engineering, University of Science and Technology Beijing, Beijing, China;School of Information Engineering, University of Science and Technology Beijing, Beijing, China
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

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Abstract

In recent years, the Biped Robot is more and more self-determining and time-sensitive, so the stability has become a very important question. But the traditional control methods can not meet it. To solve this question, Artificial Neural Network (ANN) has been brought up. Instead of most traditional control methods, Artificial Neural Network is applied widely to control the Biped Robot to walk accurately and stably. In this work, we design a control system of the Biped Robot with GA-ANN (Artificial Neural Network based on Genetic Algorithm). The GA-ANN control system adjusts the weights by the robot's Zero Moment Point (ZMP), tracks the robot's nonlinear kinetic system and keeps the robot step stably. Experiments show the stability improvement of robot using proposed algorithm.