Paper
11 October 2000 Computer vision system for an autonomous mobile robot
Xiaoqun Liao, Jin Cao, Ming Cao, Tayib Samu, Ernest L. Hall
Author Affiliations +
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoqun Liao, Jin Cao, Ming Cao, Tayib Samu, and Ernest L. Hall "Computer vision system for an autonomous mobile robot", Proc. SPIE 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, (11 October 2000); https://doi.org/10.1117/12.403759
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Calibration

Visual process modeling

Cameras

Data modeling

Imaging systems

3D image processing

Mathematical modeling

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