elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Impressum | Datenschutz | Kontakt | English
Schriftgröße: [-] Text [+]

Fully Automatic Multi-LiDAR Calibration For Self-Driving Cars

Schäfer, Jörg Peter und Schmälzle, Philipp und Andert, Franz (2021) Fully Automatic Multi-LiDAR Calibration For Self-Driving Cars. ACIMobility 2021, 2021-09-21 - 2021-09-22, Braunschweig, Deutschland.

[img] PDF
1MB

Kurzfassung

This paper addresses automatic vehicle-relative calibration of LiDAR sensors, which is essential for self-driving cars, e. g., for accurate localization, SLAM-based mapping, and sensor data fusion. While various semi-automatic techniques exist for the calibration of environment sensors, they still require a considerable amount of manual work or an expensive setup. To that, this paper presents a new algorithm for finding the mounting poses of multiple low-density LiDAR-sensors on the vehicle while minimizing manual effort. In particular, the algorithm provides co-calibration as well as extrinsic calibration relative to the IMU installed on the vehicle. The calibration process only requires some recorded data from the sensors but no special environment to compute the accurate poses. In contrast to other algorithms that register point clouds to each other, this algorithm uses a newly developed map-to-map matching method increasing the robustness of optimization processes with regard to noisy data. It works by maximizing all sensors’ consensus regarding a map simultaneously created from the recorded data. We evaluated our algorithm using a car with six mounted LiDAR-sensors and recordings from different scenarios in real urban traffic and within a testing area. Our algorithm calibrates the sensors with an expected error of less than 5 cm and less than 0.5 degrees. A key contribution is its robustness against highly noisy initial sensor configurations and its accuracy regarding the angular calibration. A visualization of the recorded data also shows calibration improvements of the mounting poses over the manual measurements.

elib-URL des Eintrags:https://elib.dlr.de/144432/
Dokumentart:Konferenzbeitrag (Vortrag)
Zusätzliche Informationen:PDF angefragt, M.Z. 05.11.21
Titel:Fully Automatic Multi-LiDAR Calibration For Self-Driving Cars
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Schäfer, Jörg PeterJoerg.Schaefer (at) dlr.dehttps://orcid.org/0000-0002-9985-5169166620283
Schmälzle, PhilippPhilipp.Schmaelzle (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Andert, FranzFranz.Andert (at) dlr.dehttps://orcid.org/0000-0002-1638-7735NICHT SPEZIFIZIERT
Datum:23 September 2021
Referierte Publikation:Nein
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:LiDAR, Multi Sensor, Calibration, Autonomous Driving
Veranstaltungstitel:ACIMobility 2021
Veranstaltungsort:Braunschweig, Deutschland
Veranstaltungsart:nationale Konferenz
Veranstaltungsbeginn:21 September 2021
Veranstaltungsende:22 September 2021
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Straßenverkehr
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V ST Straßenverkehr
DLR - Teilgebiet (Projekt, Vorhaben):V - NGC KoFiF (alt), V - D.MoVe (alt)
Standort: Berlin-Adlershof , Braunschweig
Institute & Einrichtungen:Institut für Verkehrssystemtechnik > Kooperative Systeme, BA
Institut für Verkehrssystemtechnik > Kooperative Systeme, BS
Hinterlegt von: Schäfer, Jörg Peter
Hinterlegt am:08 Nov 2021 09:05
Letzte Änderung:02 Sep 2024 09:26

Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags

Blättern
Suchen
Hilfe & Kontakt
Informationen
electronic library verwendet EPrints 3.3.12
Gestaltung Webseite und Datenbank: Copyright © Deutsches Zentrum für Luft- und Raumfahrt (DLR). Alle Rechte vorbehalten.