DocumentCode :
1911310
Title :
Neural Networks for Environmental Recognition and Navigation of a Mobile Robot
Author :
Harb, Mostapha ; Abielmona, Rami ; Naji, Kamal ; Petriu, Emil
Author_Institution :
Sch. of Inf. Technol. & Eng., Ottawa Univ., Ottawa, ON
fYear :
2008
fDate :
12-15 May 2008
Firstpage :
1123
Lastpage :
1128
Abstract :
Mobile robots could play a significant role in places where it is impossible for the human to work. In such environments, neural networks, instead of traditional methods, are suitable solutions to locally navigate and recognize the environment\´s subspaces. In order to learn and perform two important functions "environmental recognition " and "local navigation ", multi-layered neural networks are trained to process distance measurements received from a laser range-finder. These neural networks are a major component of the control system of a mobile robot dedicated for industrial applications. This paper will focus on a computer based design and test of a neural system, that includes three neural controllers for local navigation, and two neural networks for environmental recognition, fed off-line by a simulated model of a laser range-finder.
Keywords :
distance measurement; laser ranging; mobile robots; neural nets; neurocontrollers; object recognition; path planning; distance measurements; environmental recognition; laser range-finder; mobile robot; neural controllers; neural networks; robot navigation; Control systems; Distance measurement; Electrical equipment industry; Humans; Industrial control; Mobile robots; Multi-layer neural network; Navigation; Neural networks; Performance evaluation; Autonomous Robotic Navigation; Environmental Recognition; Neural Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE
Conference_Location :
Victoria, BC
ISSN :
1091-5281
Print_ISBN :
978-1-4244-1540-3
Electronic_ISBN :
1091-5281
Type :
conf
DOI :
10.1109/IMTC.2008.4547207
Filename :
4547207
Link To Document :
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