IMU-based online multi-lidar calibration

Conference item

Modern autonomous systems typically use several sensors for perception. For best performance, accurate and reliable extrinsic calibration is necessary. In this research, we propose a reliable technique for the extrinsic calibration of several lidars on a vehicle without the need for odometry estimation or fiducial markers. First, our method generates an initial guess of the extrinsics by matching the raw signals of IMUs co-located with each lidar. This initial guess is then used in ICP and point cloud feature matching which refines and verifies this estimate. Furthermore, we can use observability criteria to choose a subset of the IMU measurements that have the highest mutual information - rather than comparing all the readings. We have successfully validated our methodology using data gathered from Scania test vehicles.

Authors: Das, S; Boberg, B; Fallon, M; Chatterjee, S

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Host title: Proceedings of the 35th IEEE Intelligent Vehicles Symposium (IV 2024)
• Pages: 3227-3234
• Publication date: 2024-07-15
• Acceptance date: 2024-03-30
• Event title: 35th IEEE Intelligent Vehicles Symposium (IV 2024)
• Event location: Jeju Shinhwa World, Jeju Island, Korea
• Event website: https://ieee-iv.org/2024/
• Event start date: 2024-06-02
• Event end date: 2024-06-05
• DOI: 10.1109/iv55156.2024.10588695
• EISSN: 2642-7214
• ISSN: 1931-0587
• Language: English
• Keywords: calibration; sensor systems; laser radar; intelligent vehicles; reliability; sensors; point cloud compression