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

作　　者：Baoling Han Yuting Zhao Qingsheng Luo 

机构地区：[1]School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China [2]School of Mechatronic Engineering,Beijing Institute of Technology,Beijing 100081,China

出　　处：《Journal of Beijing Institute of Technology》2019年第3期598-605,共8页北京理工大学学报（英文版）

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

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.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.

关 键 词：DEEP Q-network (DQN) BIPED robot uneven ground WALKING STABILITY gait control 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]