Experimental Comparison of Techniques for Localization and Mapping Using a Bearing-Only Sensor (2000)
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by
Matthew Deans
,
Martial Hebert
| Citations: | 66 - 2 self |
BibTeX
@MISC{Deans00experimentalcomparison,
author = {Matthew Deans and Martial Hebert},
title = {Experimental Comparison of Techniques for Localization and Mapping Using a Bearing-Only Sensor},
year = {2000}
}
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Abstract
We present a comparison of an extended Kalman filter and an adaptation of bundle adjustment from computer vision for mobile robot localization and mapping using a bearing-only sensor. We show results on synthetic and real examples and discuss some advantages and disadvantages of the techniques. The comparison leads to a novel combination of the two techniques which results in computational complexity near Kalman filters and performance near bundle adjustment on the examples shown.
