LiDAR-to-Vehicle Calibration of Arbitrary Sensor Setups via Object Reconstruction
To begin, prepare the PCD files (in the sensor frame) for each sensor, following the example provided in the /input
directory.
The corresponding vehicle poses must be specified for each pcd in the /input/ego_poses.yaml
file.
For the poses, we expect the coordinate system (x-forward, y-left, z-up).
The poses follow the schema
- x (translation)
- y (translation)
- z (translation)
- x (quat)
- y (quat)
- z (quat)
- w (quat)
The config file currently has four entries:
- Initial Transformations: Represents the initial roll, pitch, yaw angles as well as the translation vector of both sensors.
- Target position: The parameters
min_bound
andmax_bound
define the global position of the target in all point clouds.
A Dockerfile is provided for CaLiV:
You can build the Docker file with a defined <tag>
:
docker build -t caliv:latest -f docker/Dockerfile .
Then run the calibration with:
docker run -v $(pwd)/output:/app/output -it caliv:latest
The results, namely the corrected LiDAR transformations are saved in the /output
path.