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Authors: Stephan Sehestedt and Frank E. Schneider

Affiliation: Research Establishment for Applied Sciences (FGAN), Germany

ISBN: 978-972-8865-60-3

Keyword(s): Monte Carlo Localization, MCL, Symmetric Environments, Two-Stage Sampling.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Mobile Robots and Autonomous Systems ; Robotics and Automation

Abstract: The localization problem is a central issue in mobile robotics. Monte Carlo Localization (MCL) is a popular method to solve the localization problem for mobile robots. However, usual MCL has some shortcomings in terms of computational complexity, robustness and the handling of highly symmetric environments. These three issues are adressed in this work. We present three Monte Carlo localization algorithms as a solution to these problems. The focus lies on two of these, which are especially suitable for highly symmetric environments, for which we introduce two-stage sampling as the resampling scheme.

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Paper citation in several formats:
Sehestedt S.; E. Schneider F. and (2006). MONTE CARLO LOCALIZATION IN HIGHLY SYMMETRIC ENVIRONMENTS.In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 249-254. DOI: 10.5220/0001215802490254

@conference{icinco06,
author={Stephan Sehestedt and Frank {E. Schneider}},
title={MONTE CARLO LOCALIZATION IN HIGHLY SYMMETRIC ENVIRONMENTS},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={249-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001215802490254},
isbn={978-972-8865-60-3},
}

TY - CONF

JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - MONTE CARLO LOCALIZATION IN HIGHLY SYMMETRIC ENVIRONMENTS
SN - 978-972-8865-60-3
AU - Sehestedt, S.
AU - E. Schneider, F.
PY - 2006
SP - 249
EP - 254
DO - 10.5220/0001215802490254

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