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JRM Vol.33 No.3 pp. 619-628
doi: 10.20965/jrm.2021.p0619
(2021)

Paper:

Optimal Muscular Arrangement Using Genetic Algorithm for Musculoskeletal Potential Method with Muscle Viscosity

Hitoshi Kino*, Hiroaki Ochi**, and Kenji Tahara***

*Department of Mechanical and Systems Engineering, Chukyo University
101-2 Yagoto Honmachi, Showa-ku, Nagoya, Aichi 466-8666, Japan

**Department of Mechanical Engineering, Sanyo-Onoda City University
1-1-1 Daigakudori, Sanyo-Onoda-shi, Yamaguchi 756-0884, Japan

***Department of Mechanical Engineering, Kyushu University
744 Moto-oka, Nishi-ku, Fukuoka 819-0395, Japan

Received:
November 16, 2020
Accepted:
February 10, 2021
Published:
June 20, 2021
Keywords:
musculoskeletal structure, muscular arrangement, muscle viscosity, optimization, genetic algorithm
Abstract

Muscle contractions (or equivalent mechanical elements) are responsible for joint movement in systems with musculoskeletal structure. Because muscles can only transmit force in the tensile direction in such systems, the internal force exists between the muscles. By utilizing the potential field generated by the internal force, the musculoskeletal potential method makes it possible to control the position without complex real-time calculations or sensory feedback by entering step-inputs of the balanced internal force at the target posture. However, the conditions of convergence to the target posture strongly depend on muscular arrangement. Previous studies have elucidated the mathematical conditions of the muscular arrangement; however, they provide sufficient conditions that must be satisfied by the muscular arrangement to converge to the target posture, which do not necessarily lead to optimal muscular arrangement conditions. This study proposes a method to determine the optimal muscular arrangement of a two-joint six-muscle system, wherein muscle viscosity is considered, that uses a genetic algorithm and an evaluation function considering the motion response time. The effect of the obtained muscular arrangement is verified in a simulation.

Parameters of muscular arrangement

Parameters of muscular arrangement

Cite this article as:
H. Kino, H. Ochi, and K. Tahara, “Optimal Muscular Arrangement Using Genetic Algorithm for Musculoskeletal Potential Method with Muscle Viscosity,” J. Robot. Mechatron., Vol.33 No.3, pp. 619-628, 2021.
Data files:
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