Litcius/Paper detail

Extrinsic Calibration of Multiple LiDARs of Small FoV in Targetless Environments

Xiyuan Liu, Fu Zhang

2021IEEE Robotics and Automation Letters46 citationsDOI

Abstract

The integration of multiple solid state LiDARs could achieve similar performance as a spinning LiDAR, by focusing on the dedicated area of interests. However, due to their small FoV settings, it is either required to rely on external sensors or form FoV overlaps to calibrate the extrinsic parameters between multiple LiDAR units. To overcome such limitations, we develop a targetless calibration method, which creates FoV overlaps (hence co-visible features) through movements and constructs a factor graph to resolve the constraints between LiDAR poses and extrinsic parameters. By solving the formulated problem with graph optimization, our proposed method could calibrate the extrinsic of LiDARs with few or even no overlapped FoVs, meanwhile, produce a globally consistent point cloud map. Experiments on different sensor setups and scenes have demonstrated the accuracy and robustness of our proposed approach.

Topics & Concepts

LidarRobustness (evolution)Point cloudComputer scienceCalibrationSpinningComputer visionArtificial intelligenceGraphRemote sensingGeologyEngineeringMathematicsBiochemistryChemistryTheoretical computer scienceGeneMechanical engineeringStatisticsRobotics and Sensor-Based LocalizationAdvanced Optical Sensing TechnologiesRemote Sensing and LiDAR Applications