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  Robust Localization based on Radar Signal Clustering

Schuster, F., Wörner, M., Keller, C., Haueis, M., & Curio, C. (2016). Robust Localization based on Radar Signal Clustering. In IEEE Intelligent Vehicles Symposium (IV 2016) (pp. 839-844). Piscataway, NJ, USA: IEEE.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-7A94-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-1880-1
Genre: Conference Paper

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 Creators:
Schuster, F, Author
Wörner, M, Author
Keller, CG, Author
Haueis, M, Author
Curio, C1, 2, 3, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              
3Project group: Cognitive Engineering, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_2528702              

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 Abstract: Significant advances have been achieved in mobile robot localization and mapping in dynamic environments, however these are mostly incapable of dealing with the physical properties of automotive radar sensors. In this paper we present an accurate and robust solution to this problem, by introducing a memory efficient cluster map representation. Our approach is validated by experiments that took place on a public parking space with pedestrians, moving cars, as well as different parking configurations to provide a challenging dynamic environment. The results prove its ability to reproducibly localize our vehicle within an error margin of below 1 with respect to ground truth using only point based radar targets. A decay process enables our map representation to support local updates.

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 Dates: 2016-06
 Publication Status: Published in print
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 Identifiers: DOI: 10.1109/IVS.2016.7535485
BibTex Citekey: SchusterWKHC2016
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Title: IEEE Intelligent Vehicles Symposium (IV 2016)
Place of Event: Gothenburg, Sweden
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Title: IEEE Intelligent Vehicles Symposium (IV 2016)
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 839 - 844 Identifier: ISBN: 978-1-5090-1821-5