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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9751

Title: Entrainment-enhanced Neural Oscillator for Imitation Learning
Authors: Yang, Woosung
Chong, Nak Young
You, Bum Jae
Keywords: Biologically inspired control
Neural oscillator
Imitation learning
Self-adjusting adaptor
Issue Date: 2006-08
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: 2006 IEEE International Conference on Information Acquisition
Start page: 218
End page: 223
DOI: 10.1109/ICIA.2006.305998
Abstract: To achieve biologically inspired robot control architectures based on neural oscillator networks, goal-directed imitation is addressed with respect to the problem of motion generation. It would be desirable to easily acquire appropriate motion patterns for skill learning between dissimilar bodies to attain the goal of the demonstrated motion. This requires neural oscillator networks to adapt to the non-periodic nature of arbitrary input patterns exploiting their entrainment properties. However, even in the most widely-used Matsuoka oscillator, when an unknown quasi-periodic or non-periodic signal is applied, its output signal is not always closely entrained. Therefore, current neural oscillator models may not be applied to the proposed goal-directed imitation for skill learning. To solve this problem, a supplementary term is newly included in the equation of Matsuoka oscillator. We verify general properties of the proposed model of the neural oscillator and illustrate in particular its enhanced entrainment by numerical simulation. We also show the possibility of controlling dynamic responses of oscillator-coupled mechanical systems. Technical implications of the results are discussed.
Rights: Copyright (C) 2006 IEEE. Reprinted from 2006 IEEE International Conference on Information Acquisition, 2006, 218-223. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
URI: http://hdl.handle.net/10119/9751
Material Type: publisher
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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