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Landmark based radar SLAM using graph optimization

  • On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.

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Metadaten
Author of HS ReutlingenCurio, Cristóbal
DOI:https://doi.org/10.1109/ITSC.2016.7795967
ISBN:978-1-5090-1889-5
Erschienen in:IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016
Publisher:IEEE
Place of publication:Piscataway, NJ
Document Type:Conference Proceeding
Language:English
Year of Publication:2016
Page Number:6
First Page:2559
Last Page:2564
DDC classes:620 Ingenieurwissenschaften und Maschinenbau
Open Access?:Nein
Licence (German):License Logo  Lizenzbedingungen IEEE