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JRM Vol.24 No.4 pp. 657-665
doi: 10.20965/jrm.2012.p0657
(2012)

Paper:

Feasibility Check of an Assist System Through the Simulation of Bipedal Walking Using a CPG

Tomohito Takubo*, Yohei Fukano**, Kenichi Ohara**,
Yasushi Mae**, and Tatsuo Arai**

*Department of Physical Electronics and Informatics, Graduate School of Engineering Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan

**Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan

Received:
May 9, 2011
Accepted:
February 6, 2012
Published:
August 20, 2012
Keywords:
bipedal walking simulation, wearable mobile base, assist system, sole shape, CPG
Abstract

A wearable mobile-base Walking Assist System (WAS) is simulated in this paper with the bipedal simulator we developed. The simulator employs a Central Pattern Generator (CPG) for bipedal walking pattern generation. The CPG-based walking pattern is one of the candidates for simulating human walking. Average Japanese body dimension data is applied to the bipedal model so that walking efficiency can be evaluated using the simulator. The effectiveness of the proposed simulator is confirmed by comparing real human walking and simulated walking in terms of the shape of the swing leg trajectory, data from the pressure sensor, and the feasibility of the prototype WAS. A prototype is developed and experimental results show the effectiveness of the bipedal simulator.

Cite this article as:
T. Takubo, Y. Fukano, K. Ohara, <. Mae, and T. Arai, “Feasibility Check of an Assist System Through the Simulation of Bipedal Walking Using a CPG,” J. Robot. Mechatron., Vol.24, No.4, pp. 657-665, 2012.
Data files:
References
  1. [1] T. Takubo, Y. Fukano, K. Ohara, Y. Mae, and T. Arai, “Wearable Mobile Base Walking Assist System Based on Human Intention,” 2011 JSME Conf. on Robotics and Mechatronics, 2A1-E09, 2011 (in Japanese).
  2. [2] T. Takubo, Y. Fukano, K. Ohara, Y. Mae, and Tatsuo Arai, “Simulation of bipedal walking based on CPG for the feasibility check of assist system,” Intelligent System Symposium – Fuzzy, AI, Neural Network applications technologies (FAN 2011), OS-10, 2011 (in Japanese).
  3. [3] Y. Fukano, T. Takubo, K. Ohara, Y. Mae, and T. Arai, “Simulation of bipedal walking based on CPG for Clogs-type Sole Shape,” The 5th Int. Conf. on Advanced Mechatronics (ICAM 2010), pp. 681-686, 2010.
  4. [4] M. Chen, J. Yan, and Y. Xu, “Gait Pattern Classification with Integrated Shoes,” Proc. of the 2009 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 833-839, 2009.
  5. [5] H. R. Branthwaite, C. J. Payton, and N. Chockalingam, “The effect of simple insoles on three-dimensional foot motion during normal walking,” Clinical Biomechanics, Vol.19, pp. 972-977, 2004.
  6. [6] K. Okuda, S.-Y. Yeh, C.-I. Wu, K.-H. Chang, and H.-H. Chu, “The GETA Sandals: A Footprint Location Tracking System,”Workshop on Location- and Context-Awareness (LoCa 2005), pp. 120-131, 2005.
  7. [7] T.Mori, Y. Nakamura, M. Sato, and S. Ishii, “Reinforcement Learning for CPG-driven Biped Robot,” Nineteenth National Conf. on Artificial Intelligence (AAAI 2004), pp. 623-630, 2004.
  8. [8] S. Miyakoshi, “Memory based control of bipedal walking robot with round foot profile,” 11th Robotics Symposia, pp. 147-152, 2006 (in Japanese).
  9. [9] K. Hyodo, S. Mikami, and S. Suzuki, “Outdoor Environments Walking by Biped Passive DynamicWalker with Constraint Mechanism,” J. of Robotics and Mechatronics, Vol.22, No.3, pp. 363-370, 2010.
  10. [10] T. Iijima, “Anatomy of the Human Body,”Works Corporation, 2003 (in Japanese).
  11. [11] M. Ae, H.-P. Tang, and T. Yokoi, “Estimation of Inertia Properties of the Body Segments in Japanese Athletes,” Society of Biomechanisms, Vol.11, pp. 23-33, 1992 (in Japanese).
  12. [12] S. Kajita, K. Kaneko, M. Morisawa, S. Nakaoka, and H. Hirukawa, “ZMP-based Biped Running Enhanced by Toe Springs,” Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 3963-3969, 2007.
  13. [13] J. Yanaguchi, A. Takanishi, and I. Kato, “Development of Biped Walking Robot Compensating for Three-Axis Moment by Trunk Motion,” Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, p. 561, 1993.
  14. [14] S. Kajita and K. Tani, “Experimental study of biped dynamic walking in the linear inverted pendulum mode,” Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 2885-2891, 1995.
  15. [15] G. Taga, Y. Yamaguchi, and H. Shimizu, “Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment,” Biol. Cybern., Vol.65, pp. 147-159, 1991.
  16. [16] K. Matsuoka, “Mechanisms of Frequency and Pattern Control in the Neural Rhythm Generators,” Biological Cybernetics, Vol.56, pp. 345-353, 1987.
  17. [17] M. Vukobratovic, B. Borovac, and D. Surdilovic, “Zero Moment Point – Proper Interpretation and New Applications,” Proc. of IEEE-RAS Int. Conf. on Humanoid Robots, pp. 237-244, 2001.
  18. [18] T.Mori, Y. Nakamura, M. Sato, and S. Ishii, “Reinforcement Learning for CPG-driven Biped Robot,” Nineteenth national conf. on artificial intelligence (AAAI2004), pp. 623-630, 2004.

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