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Improved inverse kinematics and dynamics model research of general parallel mechanisms

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Abstract

Since the classical kinematics model of parallel manipulators cannot accurately reflect the angular velocity and angular acceleration of the limbs, an improved kinematics model is proposed and an inverse dynamic model of the general parallel manipulator is derived based on the improved kinematics model. This paper proves that the shortcoming of the classical kinematics model is that a single model cannot accurately describe the movement of several types of branches in a parallel manipulator. Combined with the principle of angular velocity superposition and vector chain method, the improved kinematic models of the general parallel manipulator’s several typical limbs are derived. Then, an explicit inverse dynamic model of a general parallel robot is established based on the principle of virtual work. Finally, to describe the effectiveness of the improved model, we analyzed a new type of UP+SPR+SPU parallel manipulator. The improved models had higher accuracy than the classical models through the comparison.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (U1713219), the European Commission Marie Skodowska-Curie SMOOTH (Smart Robots for Fire-fighting) Project under Grant H2020-MSCA-RISE-2016-734875, and the Science and Technology (S&T) Program of Hebei under Grant 19211820D and E2020103001, Hebei Natural Science Foundation (E2021203018).

Author information

Authors and Affiliations

  1. Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, 066004, China

    Xingchao Zhang, Hongbo Wang, Jianye Niu, Junjie Tian, Shanshan Li & Yuansheng Ning

  2. Key Laboratory of Advanced Forging and Stamping Technology and Science, Yanshan University, Ministry of Education of China, Qinhuangdao, 066004, China

    Xingchao Zhang, Jianye Niu, Junjie Tian, Shanshan Li & Yuansheng Ning

  3. Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China

    Hongbo Wang

  4. College of Vehicles and Energy, Yanshan University, Qinhuangdao, Hebei, 066004, China

    Yu Rong

Authors
  1. Xingchao Zhang
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  2. Hongbo Wang
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  3. Yu Rong
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  4. Jianye Niu
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  5. Junjie Tian
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  6. Shanshan Li
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  7. Yuansheng Ning
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Corresponding author

Correspondence to Hongbo Wang.

Additional information

Xingchao Zhang received the M.S. in Mechanical Engineering from Hebei Normal University of Science & Technology, China, in 2019. He is currently pursuing the doctorate in Mechatronic Engineering at Yanshan University, China. His main research interests are kinematics and dynamics of parallel robots.

Hongbo Wang received his B.S. and M.S. from Institute of Northeast Heavy Machinery, Qiqihar, China, in 1982 and 1986, respectively. His Ph.D. is from Nagasaki University, Nagasaki, Japan in 1997. Since 2009, he has been with Yanshan University, Qinhuangdao, China as a Professor. His current research interests are in rehabilitation robot and assisting robot for the disabled and the elderly.

Yu Rong has a B.S. in Mechanical Engineering, M.S. and Ph.D. in Mechatronic Engineering from Yanshan University, Qinhuangdao, China, in 2005, 2008, and 2015, respectively. He is currently a lecturer with Yanshan University, China. His research interests include parallel mechanism, robotics.

Jianye Niu received his B.S. in Mechanical Engineering, M.S. and Ph.D. in Mechatronic Engineering from Yanshan University, Qinhuangdao, China, in 2005, 2008, and 2019, respectively. He is currently a postdoctoral researcher with the School of Mechanical Engineering, Hebei University of Technology, Tianjin, China. His research interests include parallel mechanism and its application, rehabilitation robot, mechanical engineering, and artificial neural network.

Junjie Tian received the M.S. in Chemical Process Equipment from Tianjin University, China, in 2018. He is currently pursuing the doctorate in Mechatronic Engineering at Yanshan University, China. His current research interests include rehabilitation robot, robotic compliance control.

Shanshan Li is currently a Ph.D. candidate in Mechanical Engineering, Yanshan University, China. She received her Master’s in Mechanical engineering in Hebei Normal University of Science & Technology, China, in 2019. Her current research interests include rehabilitation robot, mechanical engineering.

Yuansheng Ning received the M.S. in Mechanical Engineering from Taiyuan University of Science and Technology, China, in 2020. He is currently pursuing the doctorate in Mechatronic Engineering at Yanshan University, China. His current research interests include rehabilitation robot, robot motion planning and control, robotic compliance control, etc.

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Zhang, X., Wang, H., Rong, Y. et al. Improved inverse kinematics and dynamics model research of general parallel mechanisms. J Mech Sci Technol 37, 943–954 (2023). https://doi.org/10.1007/s12206-023-0134-1

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  • DOI: https://doi.org/10.1007/s12206-023-0134-1

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