An Optimal Pose Estimator for Map-based Mobile Robot Dynamic Localization: Experimental Comparison with the EKF (2001)
| Venue: | in IEEE International Conference on Robotics and Automation (ICRA |
BibTeX
@INPROCEEDINGS{Gil01anoptimal,
author = {Borges Aldon Gil and G. A. Borges and M. -j. Aldon and T. Gil},
title = {An Optimal Pose Estimator for Map-based Mobile Robot Dynamic Localization: Experimental Comparison with the EKF},
booktitle = {in IEEE International Conference on Robotics and Automation (ICRA},
year = {2001}
}
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Abstract
Theoretical solutions based on the matching of 2-D range measurements with a map of the environment have been proposed to solve the robot localization problem. However, most of them have not been experimented in real conditions: the robot was stopped or it moved slowly during range data acquisition, and the environment was supposed to be static. In this paper, we propose and evaluate a dynamic localization method based on feature matching. Experiments carried out in real cluttered indoor environments including people and unknown obstacles show the good performance of the proposed algorithm against the classical solution based on Kalman filtering. 1
