Recognition of intersections in corridor environments

Abstract

This project is a part of a general study of exploratory navigation by a vision-guided mobile robot maneuvering in a large, unknown, dynamic environment such as an underground mine complex. As its way of finding its way around is based on intersections, our problem is to learn and to recognize images representing intersections represented by a gray-scale 360/spl deg/ panoramic view. We propose a multilayer neural network to make associations between these representations (as input) and indexes corresponding to encountered intersections (as output).