Walking Stability Control Method for Biped Robot on Uneven Ground Based on Deep Q-Network

作     者：Baoling Han Yuting Zhao Qingsheng Luo 

作者机构：School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China School of Mechatronic EngineeringBeijing Institute of TechnologyBeijing 100081China 

出 版 物：《Journal of Beijing Institute of Technology》 (北京理工大学学报（英文版）)

年 卷 期：2019年第28卷第3期

页      面：598-605页

核心收录：

学科分类：080202[工学-机械电子工程] 08[工学] 0804[工学-仪器科学与技术] 0802[工学-机械工程] 

基　　金：Supported by the National Ministries and Research Funds(3020020221111) 

主　　题：deep Q-network (DQN) biped robot uneven ground walking stability gait control 

摘      要：A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture adjustment. A robot is taken as an agent and trained to walk steadily on an uneven surface with obstacles, using a simple reward function based on forward progress. The reward-punishment (RP) mechanism of the DQN algorithm is established after obtaining the offline gait which was generated in advance foot trajectory planning. Instead of implementing a complex dynamic model, the proposed method enables the biped robot to learn to adjust its posture on the uneven ground and ensures walking stability. The performance and effectiveness of the proposed algorithm was validated in the V-REP simulation environment. The results demonstrate that the biped robot s lateral tile angle is less than 3° after implementing the proposed method and the walking stability is obviously improved.