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Proceedings Paper

Self-localization algorithm for mobile robot based on the omni-directional sensor
Author(s): Tongwei Lu; Hui Yan; Dan Zhou
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Paper Abstract

In this paper, a simple but effective method for robot self-localization is presented. The spatial neighborhood constraint is incorporated into the preprocessing of the image segmentation. Then it uses a closed cycle with rectification and Hough detection to find the boundary and corners. Depending on the actual size of surrounding environment and the white lines and corners detected last step, the robot can maintain self-localization through two methods. One method uses the two lines, and the other method used triangulation. Finally, a weight value is set between the two methods to realize the self-localization.Actual image sequence from the robot is tested. The robot can be placed anywhere in the environment. The final self-localization results on very different images with significant light change and noise are promising.

Paper Details

Date Published: 8 December 2011
PDF: 6 pages
Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030U (8 December 2011); doi: 10.1117/12.901919
Show Author Affiliations
Tongwei Lu, Wuhan Institute of Technology (China)
Hubei Province Key Lab. of Intelligent Robot (China)
Hui Yan, Wuhan Institute of Technology (China)
Dan Zhou, Wuhan Institute of Technology (China)

Published in SPIE Proceedings Vol. 8003:
MIPPR 2011: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Nong Sang, Editor(s)

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