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Proceedings Paper

Computer vision system for an autonomous mobile robot
Author(s): Xiaoqun Liao; Jin Cao; Ming Cao; Tayib Samu; Ernest L. Hall
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Paper Abstract

The purpose of this paper is to compare three methods for 3- D measurements of line position used for the vision guidance to navigate an autonomous mobile robot. A model is first developed to map 3-D ground points into image points to be developed using homogeneous coordinates. Then using the ground plane constraint, the inverse transformation that maps image points into 3-D ground points is determined. And then the system identification problem is solved using a calibration device. Calibration data is used to determine the model parameters by minimizing the mean square error between model and calibration points. A novel simplification is then presented which provides surprisingly accurate results. This method is called the magic matrix approach and uses only the calibration data. A more standard variation of this approach is also considered. The significance of this work is that it shows that three methods that are based on 3-D measurements may be used for mobile robot navigation and that a simple method can achieve accuracy to a fraction of an inch which is sufficient in some applications.

Paper Details

Date Published: 11 October 2000
PDF: 10 pages
Proc. SPIE 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, (11 October 2000); doi: 10.1117/12.403759
Show Author Affiliations
Xiaoqun Liao, Univ. of Cincinnati (United States)
Jin Cao, Univ. of Cincinnati (United States)
Ming Cao, Univ. of Cincinnati (United States)
Tayib Samu, Univ. of Cincinnati (United States)
Ernest L. Hall, Univ. of Cincinnati (United States)

Published in SPIE Proceedings Vol. 4197:
Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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