Global localization of vehicles using local pole patterns

verfasst von: Claus Brenner
Abstract: Accurate and reliable localization is an important requirement for autonomous driving. This paper investigates an asymmetric model for global mapping and localization in large outdoor scenes. In the first stage, a mobile mapping van scans the street environment in full 3D, using high accuracy and high resolution sensors. From this raw data, local descriptors are extracted in an offline process and stored in a global map. In the second stage, vehicles, equipped with simple, inaccurate sensors are assumed to be able to recover part of these descriptors which allows them to determine their global position. The focus of this paper is on the investigation of local pole patterns. A descriptor is proposed which is tolerant with regard to missing data, and performance and scalability are considered. For the experiments, a large, dense outdoor LiDAR scan with a total length of 21.7 km is used.
Organisationseinheit(en): Institut für Kartographie und Geoinformatik
Typ: Aufsatz in Konferenzband
Seiten: 61-70
Anzahl der Seiten: 10
Publikationsdatum: 2009
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Theoretische Informatik, Allgemeine Computerwissenschaft
Elektronische Version(en): https://doi.org/10.1007/978-3-642-03798-6_7 (Zugang: Geschlossen)

BibTeX

@inproceedings{eead460e2ec24467844966a4d1c61637,
title = "Global localization of vehicles using local pole patterns",
abstract = "Accurate and reliable localization is an important requirement for autonomous driving. This paper investigates an asymmetric model for global mapping and localization in large outdoor scenes. In the first stage, a mobile mapping van scans the street environment in full 3D, using high accuracy and high resolution sensors. From this raw data, local descriptors are extracted in an offline process and stored in a global map. In the second stage, vehicles, equipped with simple, inaccurate sensors are assumed to be able to recover part of these descriptors which allows them to determine their global position. The focus of this paper is on the investigation of local pole patterns. A descriptor is proposed which is tolerant with regard to missing data, and performance and scalability are considered. For the experiments, a large, dense outdoor LiDAR scan with a total length of 21.7 km is used.",
author = "Claus Brenner",
year = "2009",
doi = "10.1007/978-3-642-03798-6_7",
language = "English",
isbn = "3642037976",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "61--70",
booktitle = "Pattern Recognition - 31st DAGM Symposium, Proceedings",
note = "31st Annual Symposium of the Deutsche Arbeitsgemeinschaft fur Mustererkennung, DAGM 2009 ; Conference date: 09-09-2009 Through 11-09-2009",
}