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Robust localization based on radar signal clustering

  • 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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Metadaten
Author of HS ReutlingenCurio, Cristóbal
DOI:https://doi.org/10.1109/IVS.2016.7535485
ISBN:978-1-5090-1821-5
Erschienen in:2016 IEEE Intelligent Vehicles Symposium (IV) Gothenburg, Sweden, June 19-22, 2016
Publisher:IEEE
Place of publication:New York, NY
Document Type:Conference Proceeding
Language:English
Year of Publication:2016
Page Number:6
First Page:839
Last Page:844
DDC classes:620 Ingenieurwissenschaften und Maschinenbau
Open Access?:Nein
Licence (German):License Logo  Lizenzbedingungen IEEE