| 基于深度强化学习的双足机器人斜坡步态控制方法 |
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| 引用本文： | 吴晓光, 刘绍维, 杨磊, 邓文强, 贾哲恒. 基于深度强化学习的双足机器人斜坡步态控制方法. 自动化学报, 2021, 47(8): 1976−1987 doi: 10.16383/j.aas.c190547 |
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| 作者姓名： | 吴晓光 刘绍维 杨磊 邓文强 贾哲恒 |
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| 作者单位： | 1.燕山大学电气工程学院 秦皇岛 066004 |
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| 基金项目： | 国家自然科学基金(61503325), 中国博士后科学基金(2015M581316)资助 |
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| 摘 要： | 为提高准被动双足机器人斜坡步行稳定性,本文提出了一种基于深度强化学习的准被动双足机器人步态控制方法.通过分析准被动双足机器人的混合动力学模型与稳定行走过程,建立了状态空间、动作空间、episode过程与奖励函数.在利用基于DDPG改进的Ape-X DPG算法持续学习后,准被动双足机器人能在较大斜坡范围内实现稳定行走.仿...
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| 关 键 词： | 准被动双足机器人 深度强化学习 步态控制 步行稳定性 |
| 收稿时间： | 2019-07-23 |
A Gait Control Method for Biped Robot on Slope Based on Deep Reinforcement Learning |
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| Wu Xiao-Guang, Liu Shao-Wei, Yang Lei, Deng Wen-Qiang, Jia Zhe-Heng. A gait control method for biped robot on slope based on deep reinforcement learning. Acta Automatica Sinica, 2021, 47(8): 1976−1987 doi: 10.16383/j.aas.c190547 |
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| Authors: | WU Xiao-Guang LIU Shao-Wei YANG Lei DENG Wen-Qiang JIA Zhe-Heng |
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| Affiliation: | 1. School of Electrical Engineering, Yanshan University, Qinhuangdao 066004 |
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| Abstract: | In order to improve the walking stability on slope of the quasi-passive biped robot, in this paper, we proposed a gait control method for quasi-passive biped robot based on deep reinforcement learning. By analyzing the hybrid dynamics model and the stable walking process of the quasi-passive biped robot establishing the state space, action space, episode process and reward function. After learning by Ape-X DPG algorithm based on DDPG improvement, quasi-passive biped robot can achieve stable walking in a larger slope range. In the simulation, Ape-X DPG is better than DDPG + PER in both learning ability and convergence speed. Meanwhile, compared with energy shaping controller, the gait convergence of quasi-passive biped robot using Ape-X DPG is more rapid and the basins of attraction is larger, which proves that Ape-X DPG can effectively improve the walking stability of quasi-passive biped robot. |
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| Keywords: | Quasi-passive biped robot deep reinforcement learning gait control walking stability |
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