Terrain mapping and classification using neural networks

Authors:
Alberto Yukinobu Hata;Denis Fernando Wolf;Gustavo Pessin;Fernando Santos Osório
Affiliations:
University of São Paulo, São Paulo, Brazil;University of São Paulo, São Paulo, Brazil;University of São Paulo, São Paulo, Brazil;University of São Paulo, São Paulo, Brazil
Venue:
Proceedings of the 2009 International Conference on Hybrid Information Technology
Year:
2009

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Abstract

This paper describes a three-dimensional terrain mapping and classification technique to allow the operation of mobile robots in outdoor environments using laser range finders. We propose the use of a multi-layer perceptron neural network to classify the terrain into navigable, partially navigable, and non-navigable. The maps generated by our approach can be used for path planning, navigation, and local obstacle avoidance. Experimental tests using an outdoor robot and a laser sensor demonstrate the accuracy of the presented methods.