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Neuro-Fuzzy Algorithm for a Biped Robotic System

Authors: Hataitep Wongsuwarn, Djitt Laowattana

Abstract:

This paper summaries basic principles and concepts of intelligent controls, implemented in humanoid robotics as well as recent algorithms being devised for advanced control of humanoid robots. Secondly, this paper presents a new approach neuro-fuzzy system. We have included some simulating results from our computational intelligence technique that will be applied to our humanoid robot. Subsequently, we determine a relationship between joint trajectories and located forces on robot-s foot through a proposed neuro-fuzzy technique.

Keywords: Computational Intelligence, neuro-fuzzy system, biped robot, Static and Dynamic Walking, Gait Synthesis

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1083429

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References:


[1] D. J. Todd, Walking Machines : An introduction to legged robot. New York: Chapmen and Hall, 1985.
[2] M. H. Raibert, Legged Robots That Balance. Cambridge, Massachusetts : The MIT Press, 1986.
[3] S. Kajita and K. Tani, "Experimental Study of Biped Dynamic Walking," in 1995 IEEE Int. Conf. on Robotics and Automation, pp. 13- 19.
[4] H. Kazuo, H. Masato, H. Yuji and T. Toru, "The Development of Honda Humanoid Robot," in Conf. Rec. 1998 IEEE Int. Conf. on Robotics & Automation, pp. 1321-1326.
[5] M. Vokobratovic, B. Borovac,D. Surla and, D. Stokic, Biped Locomotion: Dynamics, Stability, Control and Application, Springer- Verlag, 1990.
[6] N. Suwantep, "Design for Dynamics Stability of a Humanoid Mechanism," M.S. thesis, Dept. Mechanical. Eng., King Mongut-s University of Thonburi., Bangkok, Thailand, 2002.
[7] W. T. Miller, "Real-Time Neural Network Control of a Biped Walking Robot," IEEE Control Systems Magazine, pp. 41-48, February. 1994.
[8] C. L. Shih, W. A. Gruver, and T.T Lee, "Inverse kinematics and inverse dynamics for control of a biped walking machine," in 1993 Journal Robotic System, Vol., 10, no 4, pp. 531-555.
[9] Murakami, E. Yamamoto and K. Fujimoto, "Fuzzy control of dynamic biped walking robot," in Conf. Rec. 1995 IEEE Int. Conf. Fuzzy system, pp. 77-82.
[10] J. H. Park and Y. K. Rhee, "ZMP trajectory generation for reduced trunk motions of biped robots," in Conf. Rec. 1998 IEEE Int. Conf. on Robotics and Automation, pp. 2014-2021.
[11] O. Bebek and K. Erbatur, "A fuzzy system for gait adaptation of biped walking robots," in Conf. Rec. 2003 IEEE Int. Conf. on Control Applications, pp. 669-674.
[12] H. Wongsuwarn and D. Laowattana, "Bipedal Gait Synthesizer Using Adaptive Neuro-fuzzy Network", in the First Asia International Symposium on Mechatronics (AISM 2004), Xi'an, China, September, 27-30, 2004.
[13] D. Kim, S. J. Seo and G. T. Park, "Zero moment point trajectory modeling of a biped walking robot using an adaptive neuro-fuzzy system," IEE Proc. Control Theory Application, vol. 152, pp. A-B, July 2005.
[14] H. Wongsuwarn and D. Laowattana, "Experimental Study for FIBO Humanoid Robot," in Conf. Rec. 2006 IEEE Int. Conf. Robotics, Automation and Mechatronics (accepted).
[15] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its application to modeling and control," IEEE Trans. SMC, vol. , pp. 116- 132, 1985.
[16] R. Babuska, "Neuro-fuzzy methods for modeling and identification," in Recent Advances in intelligent Paradigms and Application, pp. 161-186, Springer-Verlag, 2002.