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Mechanical Design and Dynamic Compliance Control of Lightweight Manipulator

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Abstract

In the existing modular joint design and control methods of collaborative robots, the inertia of the manipulator link is large, the dynamic trajectory planning ability is weak, the collision stop safety strategy is dependent, and the adaptability and safety to the changing environment are limited. This paper develops a six-degree-of-freedom lightweight collaborative manipulator with real-time dynamic trajectory planning and active compliance control. Firstly, a novel motor installation, joint transmission, and link design method is put forward to reduce the inertia of the links and improve intrinsic safety. At the same time, to enhance the dynamic operation capability and quick response of the manipulator, a smooth planning of position and orientation under initial/end pose and velocity constraints is proposed. The adaptability to the environment is improved by the active compliance control. Finally, experiments are carried out to verify the effectiveness of the proposed design, planning, and control methods.

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Acknowledgements

This work was supported by National Key Research and Development Program of China (No. 2018AAA 0103003), National Natural Science Foundation of China (No. 61773378), the Basic Research Program (No. JCKY*******B029), and the Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB 32050100).

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Authors and Affiliations

  1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Shao-Lin Zhang, Yue-Guang Ge, Hai-Tao Wang & Shuo Wang

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yue-Guang Ge, Hai-Tao Wang & Shuo Wang

Authors
  1. Shao-Lin Zhang
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  2. Yue-Guang Ge
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  3. Hai-Tao Wang
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  4. Shuo Wang
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Corresponding author

Correspondence to Shuo Wang.

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Colored figures are available in the online version at https://link.springer.com/journal/11633

Shao-Lin Zhang received the B. Eng. and M. Eng. degrees in mechanical science and engineering from Huazhong University of Science and Technology, China in 2010 and 2013, and the Ph. D. degree in control theory and control engineering from Institute of Automation, Chinese Academy of Sciences, China in 2019. He is currently an assistant professor with State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China.

His research interests include intelligent robot system and automation systems.

Yue-Guang Ge received the B. Eng. degree in computer science and technology from Northeastern University, China in 2006, the M. Eng. degree in computer software and theory from North China Electric Power University, China in 2014. He is a Ph. D. degree candidate in control theory and control engineering at University of Chinese Academy of Sciences, China.

His research interests include intelligent robot system, knowledge representation and reasoning.

Hai-Tao Wang received the B. Eng. degree in communication engineering from University of Electronic Science and technology of China, China in 2014. He is a Ph. D. degree candidate in control theory and control engineering at University of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, China.

His research interests include robot task planning and knowledge reasoning.

Shuo Wang received the B. Eng. degree in electrical engineering from the Shenyang Architecture and Civil Engineering Institute, China in 1995, the M. Eng. degree in industrial automation from Northeastern University, China in 1998, and the Ph. D. degree in control theory and control engineering from Institute of Automation, Chinese Academy of Sciences, China in 2001, respectively. He is currently a professor with State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China.

His research interests include biomimetic robot, underwater robot, and multirobot systems.

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Zhang, SL., Ge, YG., Wang, HT. et al. Mechanical Design and Dynamic Compliance Control of Lightweight Manipulator. Int. J. Autom. Comput. 18, 926–934 (2021). https://doi.org/10.1007/s11633-021-1311-2

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  • DOI: https://doi.org/10.1007/s11633-021-1311-2

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