Basic study of sensorless path tracking control based on the musculoskeletal potential method

ROBOMECH Journal

Research Article

Yoshihiro Kinjo¹  Kenji Tahara²  Hitoshi Kino³  Yuki Matsutani⁴ 

[1] Department of Intelligent Mechanical Engineering, Fukuoka Institute of Technology, 3-30-1, Wajiro-higashi, Higashi-ku, 811-0295, Fukuoka, Japan;Department of Mechanical Engineering, Kyushu University, 744 Motooka Nishi-ku, 819-0395, Fukuoka, Japan;Department of Mechanical and Systems Engineering, Chukyo University, 101-2 Yagoto Honmachi, Showa-ku, 466-8666, Nagoya, Japan;Department of Robotics, Kindai University, 1 Takaya Umenobe, 739-2116, Higashi-Hiroshima, Japan;

关键词: Feedforward;    Manipulation;    Control;    Optimization;   

DOI  :  10.1186/s40648-023-00242-2

 received in 2022-10-31, accepted in 2022-12-23,  发布年份 2022

来源: Springer

【 摘 要 】

In a musculoskeletal system, the musculoskeletal potential method utilizes the potential property generated by the internal force between muscles; posture control can be achieved by the step input of muscular tension balancing at the desired posture. The remarkable aspect of this method is that neither sensory feedback nor complicated real-time calculation is required at all. However, previous studies addressed only point-to-point control as motion control. In other words, with the focus on the convergence to the desired posture, path tracking has not been discussed. Extending the previous studies, this paper proposes a path tracking control based on a sensorless feedforward approach. The proposed method first finds the optimal set of muscular forces that can form the potential field to the desired potential shape realizing the desired path; next, inputting the obtained muscular forces into the system achieves path tracking. For verification, this paper demonstrates a case study of a musculoskeletal system with two joints and six muscles. In this case study, a constrained nonlinear programming method is used to find the optimal muscular force, and the path trackability is verified by numerical simulation.

【 授权许可】

CC BY   
© The Author(s) 2023

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