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Applied Bionics and Biomechanics
Volume 6 (2009), Issue 1, Pages 11-26

On Control of Reaching Movements for Musculo-Skeletal Redundant Arm Model

Kenji Tahara,1,3 Suguru Arimoto,2,3 Masahiro Sekimoto,2 and Zhi-Wei Luo4

1Organization for the Promotion of Advanced Research, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
2Research Organization of Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu 525-8577, Japan
3RIKEN-TRI Collaboration Centre for Human-Interactive Robot Research, Riken, 2271-130 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan
4Department of Computer Science and Systems Engineering, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 525-8577, Japan

Received 1 February 2009

Copyright © 2009 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper focuses on a dynamic sensory-motor control mechanism of reaching movements for a musculo-skeletal redundant arm model. The formulation of a musculo-skeletal redundant arm system, which takes into account non-linear muscle properties obtained by some physiological understandings, is introduced and numerical simulations are perfomed. The non-linear properties of muscle dynamics make it possible to modulate the viscosity of the joints, and the end point of the arm converges to the desired point with a simple task-space feedback when adequate internal forces are chosen, regardless of the redundancy of the joint. Numerical simulations were performed and the effectiveness of our control scheme is discussed through these results. The results suggest that the reaching movements can be achieved using only a simple task-space feedback scheme together with the internal force effect that comes from non-linear properties of skeletal muscles without any complex mathematical computation such as an inverse dynamics or optimal trajectory derivation. In addition, the dynamic damping ellipsoid for evaluating how the internal forces can be determined is introduced. The task-space feedback is extended to the ‘virtual spring-damper hypothesis’ based on the research by Arimoto et al. (2006) to reduce the muscle output forces and heterogeneity of convergence depending on the initial state and desired position. The research suggests a new direction for studies of brain-motor control mechanism of human movements.