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http://dx.doi.org/10.5302/J.ICROS.2006.12.5.473

A Global Path Planning of Mobile Robot Using Modified SOFM  

Yu Dae-Won (원광대학교 대학원)
Jeong Se-Mi (원광대학교 대학원)
Cha Young-Youp (원광대학교 기계자동차공학부)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.12, no.5, 2006 , pp. 473-479 More about this Journal
Abstract
A global path planning algorithm using modified self-organizing feature map(SOFM) which is a method among a number of neural network is presented. The SOFM uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors of the 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the opposite direction of input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.
Keywords
global path planning; self-organizing feature map(SOFM); neural network; mobile robot;
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Times Cited By KSCI : 1  (Citation Analysis)
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