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

Volume

2

fYear

1996

fDate

26-29 May 1996

Firstpage

486

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1996. Canadian Conference on

Conference_Location

Calgary, Alta.

ISSN

0840-7789

Print_ISBN

0-7803-3143-5

Type

conf

DOI

10.1109/CCECE.1996.548196

Filename

548196