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http://dx.doi.org/10.5302/J.ICROS.2005.11.2.137

A Global Path Planning of Mobile Robot by Using Self-organizing Feature Map  

Kang Hyon-Gyu (원광대학교 기계자동차공학부)
Cha Young-Youp (원광대학교 기계자동차공학부)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.11, no.2, 2005 , pp. 137-143 More about this Journal
Abstract
Autonomous mobile robot has an ability to navigate using both map in known environment and sensors for detecting obstacles in unknown environment. In general, autonomous mobile robot navigates by global path planning on the basis of already made map and local path planning on the basis of various kinds of sensors to avoid abrupt obstacles. This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map 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, 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 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; mobile robot; self-organizing feature map; neural network;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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