MOBILE ROBOT LOCALIZATION USING LINEAR SYSTEM MODEL

Xu Zezhong, Liu Jilin

Abstract

Localization is a fundamental problem for mobile robot autonomous navigation. EKF is an efficient tool for position estimation, but it suffers from linearization errors due to linear approximation of nonlinear system equations. In this paper we describe a position estimation method for mobile robot. Process and measurement equations are linear by appropriately constructing the state vector and system models. The position of mobile robot is estimated recursively based on optimal KF. It avoids linear approximation of nonlinear system equations and is free of linearization error. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser rangefinder SICK.

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Paper Citation


in Harvard Style

Zezhong X. and Jilin L. (2004). MOBILE ROBOT LOCALIZATION USING LINEAR SYSTEM MODEL . In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 972-8865-12-0, pages 243-248. DOI: 10.5220/0001136202430248


in Bibtex Style

@conference{icinco04,
author={Xu Zezhong and Liu Jilin},
title={MOBILE ROBOT LOCALIZATION USING LINEAR SYSTEM MODEL},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2004},
pages={243-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001136202430248},
isbn={972-8865-12-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - MOBILE ROBOT LOCALIZATION USING LINEAR SYSTEM MODEL
SN - 972-8865-12-0
AU - Zezhong X.
AU - Jilin L.
PY - 2004
SP - 243
EP - 248
DO - 10.5220/0001136202430248