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Special Topics in Reinforcement Learning
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 4
1025-1033

Multi-agent deep reinforcement learning tracking control for robotic manipulator based on behavior cloning

Yi Jiahao
Wang Fujie
Hu Jintao
Qin Yi
Guo Fang
Luo Junxuan
Dept. of Computer Science, Dongguan University of Technology, Dongguan Guangdong 523000, China
DOI: 10.19734/j.issn.1001-3695.2024.09.0340

Abstract

For the robotic arm trajectory tracking in different environment with nonlinear disturbances problem, this paper proposed an MDRL control method combined with BC to solve problem. The MDRL control algorithm contained a PID agent and a DDR agent. Both of agents were based on TD3 algorithm, and designed two reward functions to optimise the policy networks of two agents. The PID agent was used to output the parameters of the PID controller and then the torque was output by PID controller to increase controller tracking generality. The DDR agent directly outputed the torque to increase the interference resis-tance of the controller. To overcome the complexity of multi-agent training, this paper utilised expert experience to pre-train the PID agent by BC. Which accelerate the reward convergence of the training process. In order to verify the validity of the method, it modeled a two-degree-of-freedom robotic arm by Eulerian-Lagrangian and compared the simulation experiments in a variety environment with disturbances. The experimental results show that the proposed algorithm has the best tracking performance in variety tracking trajectories in random interference environment, which validates the effectiveness of the algorithm.

Foundation Support

国家自然科学基金资助项目(62203116,62103106)
广东省基础与应用基础研究面上项目(2024A1515010222)
广东省教育厅特色创新项目(2022KTSCX138,2022ZDZX1031)
东莞市社会发展科技项目重点项目(20231800935882)
松山湖科技特派员项目(20234430-01KCJ-G)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.09.0340
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 4
Section: Special Topics in Reinforcement Learning
Pages: 1025-1033
Serial Number: 1001-3695(2025)04-008-1025-09

Publish History

[2025-04-05] Printed Article

Cite This Article

易佳豪, 王福杰, 胡锦涛, 等. 基于行为克隆的机械臂多智能体深度强化学习轨迹跟踪控制 [J]. 计算机应用研究, 2025, 42 (4): 1025-1033. (Yi Jiahao, Wang Fujie, Hu Jintao, et al. Multi-agent deep reinforcement learning tracking control for robotic manipulator based on behavior cloning [J]. Application Research of Computers, 2025, 42 (4): 1025-1033. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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