@inproceedings{e7bd2d12f1b8478d9757d28c873ce6c5,
title = "Localization based on the Hybrid Extended Kalman Filter with a highly accurate odometry model of a mobile robot",
abstract = "This paper describes an improving method for solving localization problems with a highly accurate model of a mobile robot either in an uncertainly large-scale environment. Firstly, we motivate our approach by analyzing intensively the dead-reckoning model for the tricycle robot type. Secondly, we propose the localization algorithm based on a Hybrid Extended Kalman Filter using artificial beacons. In this paper, 3600 sensor scan is used for each observation and the odometry data is updated to estimate the robot position. Then a comparison between the real and the estimated location of beacons and analyzing of the filter's performance are taken. The simulation results show that the proposed algorithm can lead the robot to robustly navigate in uncertain environments.",
keywords = "Extended Kalman Filter, Localization, Mobile robot",
author = "Tran, {Huu Cong} and Young, {Joong Kim} and Lim, {Myo Taeg}",
year = "2008",
language = "English",
isbn = "9781424424269",
series = "HUT-ICCE 2008 - 2nd International Conference on Communications and Electronics",
pages = "311--316",
booktitle = "HUT-ICCE 2008 - 2nd International Conference on Communications and Electronics",
note = "HUT-ICCE 2008 - 2nd International Conference on Communications and Electronics ; Conference date: 04-06-2008 Through 06-06-2008",
}