Abstract
This paper presents numerical and analytical methods for synthesis of a CPG network to acquire desired locomotor patterns. The CPG network is modeled as a chain of coupled Hopf oscillators with a coupling scheme that eliminates the influence of afferent signals on amplitude of the oscillator. The numerical method converts the related CPG parameters into dynamical systems that evolve as part of the CPG network dynamics. The frequency, amplitude and phase relations of teaching signals can be encoded by the CPG network with the proposed learning rules. For direct specification of the phase relations, the expression that defines the dependence of phase difference on coupling weights is analytically derived. The ability of the numerical methods to learn instructed locomotor pattern is proved with simulations. The effectiveness of the analytical method is also validated by the numerical results.
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References
Ijspeert, A.J.: Central Pattern Generators for Locomotion Control in Animals and Robots: A Review. Neural Netw. 21, 642–653 (2008)
Guckenheimer, J., Holmes, P.: Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Springer, New York (1983)
Hoppensteadt, F.C., Izhikevich, E.M.: Weakly Connected Neural Networks. Springer, New York (1997)
Pham, Q.C., Slotine, J.J.: Stable Concurrent Synchronization in Dynamic System Networks. Neural Netw. 20, 62–77 (2007)
Iwasaki, T.: Multivariable Harmonic Balance for Central Pattern Generators. Automatica 44, 3061–3069 (2008)
Hu, Y., Tian, W., Liang, J., Wang, T.: Learning Fish-like Swimming with A CPG-based Locomotion Controller. In: IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp. 1863–1868. IEEE Press, New York (2011)
Buchli, J., Righetti, L., Ijspeert, A.J.: Engineering Entrainment and Adaptation in Limit Cycle Systems: From Biological Inspiration to Applications in Robotics. Biol. Cybern. 95, 645–664 (2006)
Righetti, L., Buchli, J., Ijspeert, A.J.: Dynamic Hebbian Learning in Adaptive Frequency Oscillators. Physica D 216, 269–281 (2006)
Buchli, J., Iida, F., Ijspeert, A.J.: Finding Resonance: Adaptive Frequency Oscilla- tors for Dynamic Legged Locomotion. In: IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp. 3903–3909. IEEE Press, New York (2006)
Buchli, J., Ijspeert, A.J.: Distributed Central Pattern Generator Model for Robotics Application Based on Phase Sensitivity Analysis. Lect. Notes Comput. Sc. 3141, 333–349 (2004)
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Hu, Y., Zhao, W., Liang, J., Wang, T. (2012). Numerical and Analytical Methods for Synthesis of Central Pattern Generators. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7508. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33503-7_34
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DOI: https://doi.org/10.1007/978-3-642-33503-7_34
Publisher Name: Springer, Berlin, Heidelberg
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