Biologically-Inspired Locomotion Controller for a Quadruped Walking Robot: Analog IC Implementation of a CPG-Based Controller

Kazuki Nakada; Tetsuya Asai; Yoshihito Amemiya

doi:10.20965/jrm.2004.p0397

single-rb.php

« previous

JRM Vol.16 No.4 pp. 397-403

doi: 10.20965/jrm.2004.p0397

(2004)

Paper:

Views over last 60 days: 526

Biologically-Inspired Locomotion Controller for a Quadruped Walking Robot: Analog IC Implementation of a CPG-Based Controller

Kazuki Nakada, Tetsuya Asai, and Yoshihito Amemiya

Department of Electrical Engineering, Hokkaido University, Kita 13 Nishi 8, Sapporo 060-8628, Japan

Received:

January 3, 2004

Accepted:

June 23, 2004

Published:

August 20, 2004

Keywords:

biologically-inspired approach, locomotion, central pattern generator, analog IC implementation

Abstract

The present paper proposes analog integrated circuit (IC) implementation of a biologically inspired controller in quadruped robot locomotion. Our controller is based on the central pattern generator (CPG), which is known as the biological neural network that generates fundamental rhythmic movements in locomotion of animals. Many CPG-based controllers for robot locomotion have been proposed, but have mostly been implemented in software on digital microprocessors. Such a digital processor operates accurately, but it can only process sequentially. Thus, increasing the degree of freedom of physical parts of a robot deteriorates the performance of a CPG-based controller. We therefore implemented a CPG-based controller in an analog complementary metal-oxide-semiconductor (CMOS) circuit that processes in parallel essentially, making it suitable for real-time locomotion control in a multi-legged robot. Using the simulation program with integrated circuit emphasis (SPICE), we show that our controller generates stable rhythmic patterns for locomotion control in a quadruped walking robot, and change its rhythmic patterns promptly.

Cite this article as:

K. Nakada, T. Asai, and Y. Amemiya, “Biologically-Inspired Locomotion Controller for a Quadruped Walking Robot: Analog IC Implementation of a CPG-Based Controller,” J. Robot. Mechatron., Vol.16 No.4, pp. 397-403, 2004.

Data files:

References

[1] The 2nd International Symposium on Adaptive Motion of Animals and Machines, Kyoto, Japan, 2003.
[2] F. Delcomyn, “Neural basis of rhythmic behavior in animals,” Science, Vol.210, pp. 492-498, 1980.
[3] F. Delcomyn, “Foundations of Neurobiology,” New York: W, H. Freeman and Co., 1997.
[4] H. Kimura, Y. Fukuoka, and K. Konaga, “Adaptive Dynamic Walking of a Quadruped Robot by Using Neural System Model,” Advanced Robotics, Vol.15, No.8, pp. 859-876, 2001.
[5] A. Billard, and A. J, Ijspeert, “Biologically inspired neural controllers for motor control in a quadruped walking robot,” in IEEEINNS International Joint Conference on Neural Networks, Italy, July 2000.
[6] H. Takemura, J. Ueda, Y. Matsumoto, and T. Ogasawara, “A Study of a Gait Generation of a Quadruped Robot Based on Rhythmic Control – Optimization of CPG Parameters by a Fast Dynamics Simulation Environment,” in Proc. the Fifth International Conference on Climbing and Walking Robots, pp. 759-766, Paris, 2002.
[7] M. A. Lewis, M. J. Harttmann, R. Etienne-Cummings, and A. H. Cohen, “Control of a robot leg with an adaptive aVLSI CPG chip,” Neurocomputing, Vol.38-40, pp. 1409-1421, 2001.
[8] M. Branciforte, G. Di Bernardo, F. Doddo, and L. Occhipinti, “Reaction-Diffusion CNN design for a new class of biologically-inspired processors in artificial locomotion applications,” in Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems, pp. 69-77, Granada, Spain, 1999.
[9] G. Brown, “On the nature of the fundamental activity of the nearvous centers: together with an anlysis of the conditioning of the rhythmic activity in progression, and a theory of the evoution of function in the nervoussystem,” J. Physiol., Vol.48, pp. 18-46, 1914.
[10] G. Taga, Y. Yamaguchi, and H. Shimizu, “Self-organaized control of bipedal locomotion by neural oscillators in unpredictable environment,” Biological Cybernetics, Vol.65, pp. 147-159, 1991.
[11] H. Nagashino, Y. Nomura, and Y. Kinouchi, “Generation and transitions of phase-locked oscillations in coupled neural oscillators,” in the 40h SICE Annual Conference, Nagoya, Japan, 2001.
[12] K. Nakada, T. Asai, and Y. Amemiya, “An analog CMOS central pattern generator for interlimb coordination in quadruped locomotion,” IEEE Tran. on Neural Networks, Vol.14, No.5, pp. 1356-1365, 2003.
[13] H. R. Wilson, and J. D. Cowan, “Excitatory and inhibitory interactions in localized populations of model neurons,” Biophys. J., Vol.12, pp. 1-24, 1972.
[14] T. Ueta, and G. Chen, “On synchronization and control of coupled Wilson-Cowan neural oscillators,” International Journal of Bifurcation and Chaos, Vol.13, No.1, pp. 163-175, 2003.
[15] F. C. Hoppensteadt, and E. M. Ihnikevich, “Weakly connected neural networks,” Springer, Heidelberg, 1997.
[16] C. A. Mead, “Analog VLSI and neural systems,” Addison-Wesley, Reading, 1989.
[17] M. Isami, and T. Fiez, Eds. “Analog VLSI: Signal and Information Processing,” McGraw-Hill, 1993.
[18] R. J. Barker, H. W. Li, and D. E. Boyce, “CMOS circuit design, layout, and simulation,” IEEE Press, 1998.
[19] T. Shibata, and T. Ohmi, “A functional MOS transistor featuring gate level weighted sum and threshold operations,” IEEE, Trans. on Electron Devices, Vol.39, No.6, pp. 1444-1445, 1990.
[20] B. A. Minch, C. Diorio, P. Hasler, and C. A. Mead, “Translinear circuits using subthreshold floating-gate MOS transistors,” Analog Integrated Circuits and Signal Processing, Vol.9, No.2, pp. 167-179, 1998.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] The 2nd International Symposium on Adaptive Motion of Animals and Machines, Kyoto, Japan, 2003.

[2] [2] F. Delcomyn, “Neural basis of rhythmic behavior in animals,” Science, Vol.210, pp. 492-498, 1980.

[3] [3] F. Delcomyn, “Foundations of Neurobiology,” New York: W, H. Freeman and Co., 1997.

[4] [4] H. Kimura, Y. Fukuoka, and K. Konaga, “Adaptive Dynamic Walking of a Quadruped Robot by Using Neural System Model,” Advanced Robotics, Vol.15, No.8, pp. 859-876, 2001.

[5] [5] A. Billard, and A. J, Ijspeert, “Biologically inspired neural controllers for motor control in a quadruped walking robot,” in IEEEINNS International Joint Conference on Neural Networks, Italy, July 2000.

[6] [6] H. Takemura, J. Ueda, Y. Matsumoto, and T. Ogasawara, “A Study of a Gait Generation of a Quadruped Robot Based on Rhythmic Control – Optimization of CPG Parameters by a Fast Dynamics Simulation Environment,” in Proc. the Fifth International Conference on Climbing and Walking Robots, pp. 759-766, Paris, 2002.

[7] [7] M. A. Lewis, M. J. Harttmann, R. Etienne-Cummings, and A. H. Cohen, “Control of a robot leg with an adaptive aVLSI CPG chip,” Neurocomputing, Vol.38-40, pp. 1409-1421, 2001.

[8] [8] M. Branciforte, G. Di Bernardo, F. Doddo, and L. Occhipinti, “Reaction-Diffusion CNN design for a new class of biologically-inspired processors in artificial locomotion applications,” in Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems, pp. 69-77, Granada, Spain, 1999.

[9] [9] G. Brown, “On the nature of the fundamental activity of the nearvous centers: together with an anlysis of the conditioning of the rhythmic activity in progression, and a theory of the evoution of function in the nervoussystem,” J. Physiol., Vol.48, pp. 18-46, 1914.

[10] [10] G. Taga, Y. Yamaguchi, and H. Shimizu, “Self-organaized control of bipedal locomotion by neural oscillators in unpredictable environment,” Biological Cybernetics, Vol.65, pp. 147-159, 1991.

[11] [11] H. Nagashino, Y. Nomura, and Y. Kinouchi, “Generation and transitions of phase-locked oscillations in coupled neural oscillators,” in the 40h SICE Annual Conference, Nagoya, Japan, 2001.

[12] [12] K. Nakada, T. Asai, and Y. Amemiya, “An analog CMOS central pattern generator for interlimb coordination in quadruped locomotion,” IEEE Tran. on Neural Networks, Vol.14, No.5, pp. 1356-1365, 2003.

[13] [13] H. R. Wilson, and J. D. Cowan, “Excitatory and inhibitory interactions in localized populations of model neurons,” Biophys. J., Vol.12, pp. 1-24, 1972.

[14] [14] T. Ueta, and G. Chen, “On synchronization and control of coupled Wilson-Cowan neural oscillators,” International Journal of Bifurcation and Chaos, Vol.13, No.1, pp. 163-175, 2003.

[15] [15] F. C. Hoppensteadt, and E. M. Ihnikevich, “Weakly connected neural networks,” Springer, Heidelberg, 1997.

[16] [16] C. A. Mead, “Analog VLSI and neural systems,” Addison-Wesley, Reading, 1989.

[17] [17] M. Isami, and T. Fiez, Eds. “Analog VLSI: Signal and Information Processing,” McGraw-Hill, 1993.

[18] [18] R. J. Barker, H. W. Li, and D. E. Boyce, “CMOS circuit design, layout, and simulation,” IEEE Press, 1998.

[19] [19] T. Shibata, and T. Ohmi, “A functional MOS transistor featuring gate level weighted sum and threshold operations,” IEEE, Trans. on Electron Devices, Vol.39, No.6, pp. 1444-1445, 1990.

[20] [20] B. A. Minch, C. Diorio, P. Hasler, and C. A. Mead, “Translinear circuits using subthreshold floating-gate MOS transistors,” Analog Integrated Circuits and Signal Processing, Vol.9, No.2, pp. 167-179, 1998.