livox_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.
![](pics/color_cloud.png)
New features in next version:
- Support spinning LiDAR
- Support muti-scenes calibration (more accuracy)
Related paper available on arxiv:
Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments
Related video: https://youtu.be/sp6PZTL2StY
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
Download Our recorded rosbag to your local path, and then change the path in calib.launch to your data path. Then directly run
roslaunch livox_camera_calib calib.launch
If you have trouble in downloading the rosbag files, you can download the same files from Baidu net-disk.
Link (链接): https://pan.baidu.com/s/197hsjmO42p5OIUjo_l4kkg
Extraction code (提取码): myfm
Record the point cloud and image msg to rosbag (15s or more for avia LiDAR). Then change the topic name in config_outdoor.yaml file
# Topic name in rosbag
PointCloudTopic: "/livox/lidar"
ImageTopic: "/camera/color/image_raw"
Modify the camera matrix and distortion coeffs in camera.yaml
Modify the initial extrinsic in config_outdoor.yaml if needed.