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Localization inside a populated parking garage by using particle filters with a map of the static environment

Raúl Rojas, S. Wahl, P. Schlumberger, M. Stampfle – 2015

For a vehicle driving safe inside a parking garage autonomously, it is necessary to build a map with its surroundings and also to localize itself within this map. This is known as Simultaneous Localization And Mapping (SLAM). To enable the vehicle to drive autonomously to an assigned parking slot, a parking area, or the exit, the vehicle also needs knowledge about the whole map of the parking garage. This map only contains static elements of the parking garage. Variable elements are not known to the parking garage and therefore are not contained in this static map. In order to reach a target, the vehicle needs to localize itself with respect to this static map. In this contribution the use of such a static map is proposed to support SLAM. This enables SLAM to determine poses related to a static map. Also the performance of SLAM is improved.

Titel
Localization inside a populated parking garage
Verfasser
Raúl Rojas, S. Wahl, P. Schlumberger, M. Stampfle
Verlag
IEEE
Schlagwörter
SLAM (robots), mobile robots, navigation, particle filtering (numerical methods) road vehicles, statistical distributions, traffic control
Datum
2015-06
Kennung
DOI: 10.1109/IVS.2015.7225669
Quelle/n
Erschienen in
Proceedings of the Intelligent Vehicles Symposium (IV), Seoul 2015
Größe oder Länge
pp. 95-100
Rechte
Copyright by IEEE. When citing this work, cite the original link.