57 lines
1.8 KiB
Markdown
57 lines
1.8 KiB
Markdown
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# Lidar to Camera Extrinsic Calibration
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The goal of this procedure is to find the extrinsic transformation between the Lidar coordinate frame and that of the camera in front of the robot:
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<p align="center">
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<img src="assets/lidar-camera-extrinsics.drawio.png" alt="image" width="60%" height="auto"/>
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</p>
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First pull the docker image:
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```bash
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docker pull koide3/direct_visual_lidar_calibration:humble
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```
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Then activate the X server connection port:
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```bash
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xhost +
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```
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and run the container with GUI support:
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```bash
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docker run \
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-it \
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--rm \
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--net host \
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--gpus all \
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-e DISPLAY=$DISPLAY \
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-v $HOME/.Xauthority:/root/.Xauthority \
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-v /path/to/input/bags:/tmp/input_bags \
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-v /path/to/save/result:/tmp/preprocessed \
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koide3/direct_visual_lidar_calibration:humble
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```
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Inside the container generate images from the LiDAR data (Preprocessing):
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```bash
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ros2 run direct_visual_lidar_calibration preprocess /path/to/bag/dir /path/to/result/dir \
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--image_topic /camera/color/image_raw \
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--points_topic /utlidar/cloud \
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--camera_model plumb_bob \
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--camera_intrinsics 379.7099304199219,320.3064270019531,379.3695983886719,243.11753845214844 \
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--camera_distortion_coeffs -0.057967256754636765,0.0704321563243866,-0.00015285948757082224,0.0006057045538909733,-0.022366832941770554
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```
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then manually select the correspondences between the 3D pointcloud and the image:
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```bash
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ros2 run direct_visual_lidar_calibration initial_guess_manual /path/to/result/dir
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```
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Finally perform a refinement step by running:
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```bash
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ros2 run direct_visual_lidar_calibration calibrate /path/to/result/dir
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```
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[](https://www.youtube.com/watch?v=FTlC9RwEVxY&t=43s)
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# Source
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This procedure has been taken from [direct_visual_lidar_calibration toolbox](https://koide3.github.io/direct_visual_lidar_calibration/).
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