This work is an extended version of livox_camera_calib, which is suitable for spinning LiDAR。

In order to apply this algorithm on spinning LIDAR(e.g:VLP16)， I add the preprocess process(FLOAM) to make the point cloud of the spinning LiDAR denser.

When you calibrate the spinning lidar and camera, record the data by holding the device(lidar and camera) stationary for a period of time and then slowly and repeatedly move the entire device in this direction to accumulate the point cloud.

ceres-slover == 1.14.0
pcl==1.8.0

cd ~/catkin_ws/src
git clone https://github.com/AFEICHINA/extended_lidar_camera_calib.git
cd ..
catkin_make
source ~/catkin_ws/devel/setup.bash

step1: doing slam to accumulate dense pointcloud.

roslaunch floam floam_XXX.launch

step2: lidar camera calibration

roslaunch livox_camera_calib calib_XXX.launch

In my test, I get better results in indoor enviroment.

LIDAR : Robosense RS-Bpearl
Camera: MindVision MV-SUA133GC-T

slam result:

map result:

calib result:

Thanks for livox_camera_calib and FLOAM.