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

arXiv: https://arxiv.org/abs/2203.03182 · HTML: https://mlsanity.com/paper/2203.03182/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 32 references that are in the map.
- First posted on arXiv 7 Mar 2022.

## Builds on (most cited first, 6 of 6)

- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator](https://mlsanity.com/paper/1708.03852/) (2017)
- [Online Temporal Calibration for Monocular Visual-Inertial Systems](https://mlsanity.com/paper/1808.00692/) (2018)
- [LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry](https://mlsanity.com/paper/1804.05178/) (2018)
- [A Novel Dual-Lidar Calibration Algorithm Using Planar Surfaces](https://mlsanity.com/paper/1904.12116/) (2019)
- [Automatic Calibration of Multiple 3D LiDARs in Urban Environments](https://mlsanity.com/paper/1905.04912/) (2019)

## Built on by (most cited first, 3 of 3)

- [OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving](https://mlsanity.com/paper/2205.14087/) (2022)
- [CaLiV: LiDAR-to-Vehicle Calibration of Arbitrary Sensor Setups](https://mlsanity.com/paper/2504.01987/) (2025)
- [Online LiDAR-Camera Extrinsic Parameters Self-checking](https://mlsanity.com/paper/2210.10537/) (2022)

## Abstract (arXiv)

Sensor-based environmental perception is a crucial part of the autonomous driving system. In order to get an excellent perception of the surrounding environment, an intelligent system would configure multiple LiDARs (3D Light Detection and Ranging) to cover the distant and near space of the car. The precision of perception relies on the quality of sensor calibration. This research aims at developing an accurate, automatic, and robust calibration strategy for multiple LiDAR systems in the general road scene. We thus propose CROON (automatiC multi-LiDAR CalibratiOn and Refinement method in rOad sceNe), a two-stage method including rough and refinement calibration. The first stage can calibrate the sensor from an arbitrary initial pose, and the second stage is able to precisely calibrate the sensor iteratively. Specifically, CROON utilize the nature characteristics of road scene so that it is independent and easy to apply in large-scale conditions. Experimental results on real-world and simulated data sets demonstrate the reliability and accuracy of our method. All the related data sets and codes are open-sourced on the Github website https://github.com/OpenCalib/LiDAR2LiDAR.