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Localization methods for a mobile robot in urban environments (2004)
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| Venue: | IEEE Transactions on Robotics |
| Citations: | 62 - 1 self |
BibTeX
@ARTICLE{Georgiev04localizationmethods,
author = {Atanas Georgiev and Peter K. Allen},
title = {Localization methods for a mobile robot in urban environments},
journal = {IEEE Transactions on Robotics},
year = {2004},
volume = {20},
pages = {851--864}
}
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Abstract
Abstract — This paper addresses the problems of building a functional mobile robot for urban site navigation and modeling with focus on keeping track of the robot location. We have developed a localization system that employs two methods. The first method uses odometry, a compass and tilt sensor, and a global positioning sensor. An extended Kalman filter integrates the sensor data and keeps track of the uncertainty associated with it. The second method is based on camera pose estimation. It is used when the uncertainty from the first method becomes very large. The pose estimation is done by matching linear features in the image with a simple and compact environmental model. We have demonstrated the functionality of the robot and the localization methods with real-world experiments. Index Terms — Mobile robots, localization, machine vision I.
Keyphrases
localization method mobile robot urban environment first method second method linear feature functional mobile robot machine vision robot location camera pose estimation urban site navigation real-world experiment extended kalman filter compact environmental model tilt sensor index term mobile robot global positioning sensor pose estimation localization system sensor data
