lidar_camera_calib is a robust, high accuracy extrinsic calibration tool between high resolution LiDAR (e.g. Livox) and camera in targetless environment. Our algorithm can run in both indoor and outdoor scenes, and only requires edge information in the scene. If the scene is suitable, we can achieve pixel-level accuracy similar to or even beyond the target based method.

An example of a outdoor calibration scenario. We color the point cloud with the calibrated extrinsic and compare with actual image. A and C are locally enlarged views of the point cloud. B and D are parts of the camera image corresponding to point cloud in A and C.

New features:

1. Support muti-scenes calibration (more accurate and robust)

Related paper available on arxiv:
Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments

Related video: https://youtu.be/e6Vkkasc4JI

Ubuntu 64-bit 16.04 or 18.04. ROS Kinetic or Melodic. ROS Installation and its additional ROS pacakge:

    sudo apt-get install ros-XXX-cv-bridge ros-xxx-pcl-conversions

Follow Eigen Installation

Follow Ceres Installation.

Follow PCL Installation. (Our code is tested with PCL1.7)

Clone the repository and catkin_make:

cd ~/catkin_ws/src
git clone https://github.com/hku-mars/livox_camera_calib.git
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash

The exmaple dataset can be download from OneDrive and BaiduNetDisk(百度网盘)

Download Our pcd and iamge file to your local path, and then change the file path in calib.yaml to your data path. Then directly run

roslaunch livox_camera_calib calib.launch

You will get the following result. (Sensor suite: Livox Avia + Realsense-D435i)

An example of single scene calibration.

Download Our pcd and iamge file to your local path, and then change the file path in multi_calib.yaml to your data path. Then directly run

roslaunch livox_camera_calib multi_calib.launch

The projected images obtained by initial extrinsic parameters. (Sensor Suite: Livox Horizon + MVS camera)

An example of multi scenes calibration. The projected image obtained by theinitial extrinsic parameters

The projected image obtained by the extrinsic parameters after rough calibration

The projected image obtained by the extrinsic parameters after fine calibration

Record the point cloud to pcd files and record image files.

Change the data path to your local data path.
Provide the instrinsic matrix and distor coeffs for your camera.

Change the params in multi_calib.yaml, name the image file and pcd file from 0 to (data_num-1).