Title :
Neural network-based recognition of mine environments
Author :
Béranger, Véronique ; Hervé, Jean-Yves
Author_Institution :
Groupe de Recherche en Perception et Robotique, Ecole Polytech., Montreal, Que., Canada
Abstract :
This project is a part of a general study of exploratory navigation by a vision-guided mobile robot manoeuvring in a large, unknown, dynamic environment such as an underground mine complex. Since the robot navigation is based on intersections, our problem is make the robot to learn and to recognize images representing intersections based on a gray-scaled 360° panoramic view. We propose a multilayer neural network to make associations between these representations and indexes corresponding to the encountered intersections
Keywords :
feedforward neural nets; image recognition; image representation; learning (artificial intelligence); mining; mobile robots; navigation; path planning; robot vision; dynamic environment; exploratory navigation; gray-scaled panoramic view; image recognition; intersections; learning process; multilayer neural network; underground mine; vision-guided mobile robot; Humans; Image recognition; Intelligent robots; Layout; Mobile robots; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pattern recognition; Robot vision systems;
Conference_Titel :
Electrical and Computer Engineering, 1996. Canadian Conference on
Conference_Location :
Calgary, Alta.
Print_ISBN :
0-7803-3143-5
DOI :
10.1109/CCECE.1996.548196