elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Fully Automatic Multi-LiDAR Calibration For Self-Driving Cars

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

[img] PDF
1MB

Abstract

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.

Item URL in elib:https://elib.dlr.de/144432/
Document Type:Conference or Workshop Item (Speech)
Additional Information:PDF angefragt, M.Z. 05.11.21
Title:Fully Automatic Multi-LiDAR Calibration For Self-Driving Cars
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schäfer, Jörg PeterJoerg.Schaefer (at) dlr.dehttps://orcid.org/0000-0002-9985-5169
Schmälzle, PhilippPhilipp.Schmaelzle (at) dlr.deUNSPECIFIED
Andert, FranzFranz.Andert (at) dlr.dehttps://orcid.org/0000-0002-1638-7735
Date:23 September 2021
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:LiDAR, Multi Sensor, Calibration, Autonomous Driving
Event Title:ACIMobility 2021
Event Location:Braunschweig, Deutschland
Event Type:national Conference
Event Dates:21.-22. Sept. 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF, V - D.MoVe
Location: Berlin-Adlershof , Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Cooperative Systems, BA
Institute of Transportation Systems > Cooperative Systems, BS
Deposited By: Schäfer, Jörg Peter
Deposited On:08 Nov 2021 09:05
Last Modified:08 Nov 2021 09:05

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.