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Sensor-based environmental perception is a crucial part of the autonomousdriving system. In order to get an excellent perception of the surroundingenvironment, an intelligent system would configure multiple LiDARs (3D LightDetection and Ranging) to cover the distant and near space of the car. Theprecision of perception relies on the quality of sensor calibration. Thisresearch aims at developing an accurate, automatic, and robust calibrationstrategy for multiple LiDAR systems in the general road scene. We thus proposeCROON (automatiC multi-LiDAR CalibratiOn and Refinement method in rOad sceNe),a two-stage method including rough and refinement calibration. The first stagecan calibrate the sensor from an arbitrary initial pose, and the second stageis able to precisely calibrate the sensor iteratively. Specifically, CROONutilize the nature characteristics of road scene so that it is independent andeasy to apply in large-scale conditions. Experimental results on real-world andsimulated data sets demonstrate the reliability and accuracy of our method. Allthe related data sets and codes are open-sourced on the Github websitehttps://github.com/OpenCalib/LiDAR2LiDAR.

CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene