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Proceedings Paper

Mobile robot navigation with vision-based neural networks
Author(s): Rafael M. Inigo; Raul E. Torres
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Paper Abstract

Mobile robot technology is spreading its use in the development of advance manufacturing systems. Methods of multi-sensory fusion data with vision, sonar and limit switches have been developed as the most flexible, but expensive approaches. Other approaches are more common such as buried wire AGV's. They decrease the cost of the mobile robot, but degrade the flexibility of the navigation system as well. This paper uses neural networks (NNs) with only one camera to obtain similar flexibility as the high cost approaches, but in a cost-efficient way. The NNs use translation and perspective information of features in images to determine the proper alignment and position of the mobile robot.

Paper Details

Date Published: 9 January 1995
PDF: 12 pages
Proc. SPIE 2352, Mobile Robots IX, (9 January 1995); doi: 10.1117/12.198984
Show Author Affiliations
Rafael M. Inigo, Univ. of Virginia (United States)
Raul E. Torres, Univ. of Virginia (United States)

Published in SPIE Proceedings Vol. 2352:
Mobile Robots IX
William J. Wolfe; Wendell H. Chun, Editor(s)

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