Experimental Comparison of Techniques for Localization and Mapping using a Bearings Only Sensor
Conference Paper, Proceedings of 7th International Symposium on Experimental Robotics (ISER '00), pp. 395 - 404, December, 2000
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.
BibTeX
@conference{Deans-2000-8159,author = {Matthew Deans and Martial Hebert},
title = {Experimental Comparison of Techniques for Localization and Mapping using a Bearings Only Sensor},
booktitle = {Proceedings of 7th International Symposium on Experimental Robotics (ISER '00)},
year = {2000},
month = {December},
pages = {395 - 404},
}
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