Go2Py/docs/utlidar-camera-calib.md

Lidar to Camera Extrinsic Calibration

First pull the docker image:

docker pull koide3/direct_visual_lidar_calibration:humble

Then activate the X server connection port:

xhost +

and run the container with GUI support:

docker run \
  -it \
  --rm \
  --net host \
  --gpus all \
  -e DISPLAY=$DISPLAY \
  -v $HOME/.Xauthority:/root/.Xauthority \
  -v /path/to/input/bags:/tmp/input_bags \
  -v /path/to/save/result:/tmp/preprocessed \
  koide3/direct_visual_lidar_calibration:humble 

Inside the container generate images from the LiDAR data (Preprocessing):

ros2 run direct_visual_lidar_calibration preprocess /path/to/bag/dir /path/to/result/dir \
  --image_topic /camera/color/image_raw \
  --points_topic /utlidar/cloud \
  --camera_model plumb_bob \
  --camera_intrinsics 379.7099304199219,320.3064270019531,379.3695983886719,243.11753845214844 \
  --camera_distortion_coeffs -0.057967256754636765,0.0704321563243866,-0.00015285948757082224,0.0006057045538909733,-0.022366832941770554

then manually select the correspondences between the 3D pointcloud and the image:

ros2 run direct_visual_lidar_calibration initial_guess_manual /path/to/result/dir

Finally perform a refinement step by running:

ros2 run direct_visual_lidar_calibration calibrate /path/to/result/dir

Source

This procedure has been taken from direct_visual_lidar_calibration toolbox.