An Extrinsic Calibration Tool for Radar, Camera and Lidar

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We present a novel open-source tool for extrinsic calibration of radar, camera and lidar. Unlike currently available offerings, our tool facilitates joint extrinsic calibration of all three sensing modalities on multiple measurements. Furthermore, our calibration target design extends existing work to obtain simultaneous measurements for all these modalities. We study how various factors of the calibration procedure affect the outcome on real multi-modal measurements of the target. Three different configurations of the optimization criterion are considered, namely using error terms for a minimal amount of sensor pairs, or using terms for all sensor pairs with additional loop closure constraints, or by adding terms for structure estimation in a probabilistic model. The experiments further evaluate how the number of calibration boards affect calibration performance, and robustness against different levels of zero mean Gaussian noise. Our results show that all configurations achieve good results for lidar to camera errors and that fully connected pose estimation shows the best performance for lidar to radar errors when more than five board locations are used.
Original languageEnglish
Title of host publicationProceedings IEEE International Conference on Robotics and Automation (ICRA 2019)
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-1-5386-6026-3
ISBN (Print)978-1-5386-6027-0
Publication statusPublished - 2019
Event2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada
Duration: 20 May 201924 May 2019


Conference2019 International Conference on Robotics and Automation, ICRA 2019

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