TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Schuster, Frank
A1  - Wörner, Markus
A1  - Keller, Christoph
A1  - Haueis, Martin
A1  - Curio, Cristóbal
T1  - Robust localization based on radar signal clustering
T2  - 2016 IEEE Intelligent Vehicles Symposium (IV) Gothenburg, Sweden, June 19-22, 2016
N2  - 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.
Y1  - 2016
SN  - 978-1-5090-1821-5
SB  - 978-1-5090-1821-5
U6  - https://doi.org/10.1109/IVS.2016.7535485
DO  - https://doi.org/10.1109/IVS.2016.7535485
SP  - 839
EP  - 844
S1  - 6
PB  - IEEE
CY  - New York, NY
ER  -