Data collection for rough terrain vehicle-Lidar calibration
Last updated
Last updated
Checkerboard is the calibration target. For small vehicles, the minimum checkerboard size is 0.6m^2. For large cars, the minimum checkerboard size is 2.4m^2. If calibrating a small car, you can print the below pdf file on a foam board at 1.0m x 0.6m. Most print shops can print this. https://drive.google.com/file/d/1mTR8HTpvROE1Pv0rmXEBVLSxs_yMDnvf?usp=sharing For car wheels, use the Aruco markers. Click here for Aruco markers.
We need an additional camera which is used as a support (external) camera. Note: The external camera should have a fixed focal length. Changing focal length / auto-focus will change the camera intrinsic parameters. A DSLR with manual fixed focal length can make a good external camera. Modern cell phone cameras all have auto-focus so should not be used as an external camera.
Stick Aruco markers to the vehicle wheels to auto-detect the wheel center. Click here for Aruco markers. Note: The ArUco markers must match the wheel position. Mismatched markers will not be recognized in the application.
Place and fix the checkerboard position in the mounted lidar's field of view. A point cloud is extracted from the mounted Lidar sensor.
Take an image from the external camera having a front-left wheel, rear-left wheel, and checkerboard in its field of view. Note: Using a tripod with the the external camera can reduce motion blur and improve calibration accuracy.
Move the external camera to a different location and take another image. Repeat the process for at least three iteration. Note: The vehicle, ArUco tags, and checkerboard should all be static during steps 4 and 5.
Now repeat the entire steps from 3 to 5 by moving the external camera to the right side of the vehicle.
Try to use aruco markers of higher length. Measure the length of the aurco marker once printed, and configure same value in the tool.
Try to make sure the aruco marker is as plain as possible. Aluminium Dibond can be used for the same purpose.
Have the checkerboard tilted to the right, this helps to detect the checkerboard edge points and then make the sparse checkerboard dense.
Use accurate intrinsic parameters for the external camera as this method mostly depends on the aruco marker detection on the wheels.