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Experimental Comparison of Techniques for Localization and Mapping using a Bearings Only Sensor

Matthew Deans and Martial Hebert
Conference Paper, Carnegie Mellon University, Proc. of the ISER '00 Seventh International Symposium on Experimental Robotics, December, 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.

BibTeX Reference
@conference{Deans-2000-8159,
title = {Experimental Comparison of Techniques for Localization and Mapping using a Bearings Only Sensor},
author = {Matthew Deans and Martial Hebert},
booktitle = {Proc. of the ISER '00 Seventh International Symposium on Experimental Robotics},
school = {Robotics Institute , Carnegie Mellon University},
month = {December},
year = {2000},
address = {Pittsburgh, PA},
}
2017-09-13T10:45:59+00:00