Trajectory planning of a manipulator based on the DDPG algorithm

Xiangyu Jing; Chuanzhi Zang; Yuqi Liu; Yu Liu; Changqing Xia

doi:10.1117/12.2661308

9 December 2022 Trajectory planning of a manipulator based on the DDPG algorithm

Xiangyu Jing, Chuanzhi Zang, Yuqi Liu, Yu Liu, Changqing Xia

Proceedings Volume 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022); 124920M (2022) https://doi.org/10.1117/12.2661308
Event: International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 2022, Wuhan, China

Abstract

Trajectory planning is one of the key technologies in the manipulator motion system, and the effectiveness of the manipulator as a whole is directly influenced by this technology. Thus, accurate and effective trajectory planning is crucial. In this study, a reinforcement learning system is used to plan a manipulator's trajectory. A trajectory planning of a manipulator based on the deep deterministic policy gradient (DDPG) method, which is easier to converge on than the Actor-Critic (AC) approach, is proposed in order to address the issue that the AC algorithm is difficult to converge on. A guiding reward function is provided in the reward function area to address the issue that the manipulator can't contact the target rapidly due to blind exploration. This can help the manipulator touch the target more quickly. In this paper, a two-degree of freedom manipulator is selected as the experimental object. The obstacle avoidance reward function based on the AC algorithm, the obstacle avoidance reward function based on the DDPG algorithm, and the obstacle avoidance reward function and guiding reward function based on the DDPG algorithm are compared. The findings demonstrate that the DDPG method converges easier than the AC algorithm, and that the directed reward function can help the manipulator avoid obstacles.

Citation Download Citation

Xiangyu Jing, Chuanzhi Zang, Yuqi Liu, Yu Liu, and Changqing Xia "Trajectory planning of a manipulator based on the DDPG algorithm", Proc. SPIE 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 124920M (9 December 2022); https://doi.org/10.1117/12.2661308

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