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Proceedings Paper

Stereo Image Ranging For An Autonomous Robot Vision System
Author(s): James R. Holten; Steven K. Rogers; Matthew Kabrisky; Steven Cross
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Paper Abstract

The principles of stereo vision for three-dimensional data acquisition are well-known and can be applied to the problem of an autonomous robot vehicle. Coincidental points in the two images are located and then the location of that point in a three-dimensional space can be calculated using the offset of the points and knowledge of the camera positions and geometry. This research investigates the application of artificial intelligence knowledge representation techniques as a means to apply heuristics to relieve the computational intensity of the low level image processing tasks. Specifically a new technique for image feature extraction is presented. This technique, the Queen Victoria Algorithm, uses formal language productions to process the image and characterize its features. These characterized features are then used for stereo image feature registration to obtain the required ranging information. The results can be used by an autonomous robot vision system for environmental modeling and path finding.

Paper Details

Date Published: 11 December 1985
PDF: 5 pages
Proc. SPIE 0579, Intelligent Robots and Computer Vision IV, (11 December 1985); doi: 10.1117/12.950834
Show Author Affiliations
James R. Holten, Air Force Institute of Technology (United States)
Steven K. Rogers, Air Force Institute of Technology (United States)
Matthew Kabrisky, Air Force Institute of Technology (United States)
Steven Cross, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 0579:
Intelligent Robots and Computer Vision IV
David P. Casasent, Editor(s)

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