Learning to categorize perceptual space of a mobile robot using Fuzzy-ART neural network
Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 2, pp. 1272 - 1277, September, 1994
Abstract
This paper deals with an application of fuzzy-ART self-organizing neural classifier to adaptive categorization of the perceptual space of a mobile robot. The aim of the research is to develop a learning system for reactive locomotion control in an unknown, cluttered environment. A qualitative description of the proposed categorization technique for a trial-and-error learning paradigm is given. Experimental results show that the method of control is efficient, when learning starts from scratch, as well as after some major disturbances of an already experienced system.
BibTeX
@conference{Dubrawski-1994-121915,author = {A. Dubrawski and P. Reignier},
title = {Learning to categorize perceptual space of a mobile robot using Fuzzy-ART neural network},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {1994},
month = {September},
volume = {2},
pages = {1272 - 1277},
}
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