Vision-Based Localization Algorithm Based on Landmark Matching, Triangulation, Reconstruction, and Comparison

Many generic position-estimation algorithms are vulnerable to ambiguity introduced by nonunique landmarks. Also, the available high-dimensional image data is not fully used when these techniques are extended to vision-based localization. This paper presents the landmark matching, triangulation, reco...

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Bibliographic Details
Main Authors: Yuen, D.C.K (Author), MacDonald, B.A (Author)
Format: Article
Language:English
Published: 2005.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Yuen, D.C.K.  |e author 
700 1 0 |a MacDonald, B.A.  |e author 
245 0 0 |a Vision-Based Localization Algorithm Based on Landmark Matching, Triangulation, Reconstruction, and Comparison 
260 |c 2005. 
856 |z Get fulltext  |u https://eprints.soton.ac.uk/262758/1/dybm-visionloc-2k5.pdf 
520 |a Many generic position-estimation algorithms are vulnerable to ambiguity introduced by nonunique landmarks. Also, the available high-dimensional image data is not fully used when these techniques are extended to vision-based localization. This paper presents the landmark matching, triangulation, reconstruction, and comparison (LTRC) global localization algorithm, which is reasonably immune to ambiguous landmark matches. It extracts natural landmarks for the (rough) matching stage before generating the list of possible position estimates through triangulation. Reconstruction and comparison then rank the possible estimates. The LTRC algorithm has been implemented using an interpreted language, onto a robot equipped with a panoramic vision system. Empirical data shows remarkable improvement in accuracy when compared with the established random sample consensus method. LTRC is also robust against inaccurate map data. 
655 7 |a Article