Rough terrain vehicle Lidar calibration

Calibrate List Page:

Click on ‘New Calibration’ on the calibration list page.

Calibration type selection:

Click on Vehicle-LiDAR calibration, to start it.

Calibration welcome page:

A welcome page with the set of instructions is shown at the beginning, just click on ‘Get started’ to go forward.

Vehicle configuration page:

Enter the calibration configuration along with the calibration name. Following are the vehicle configurations.
  • Wheelbase: Distance between left/right front wheel center and left/right rear wheel center in meters. If asked for a Wheelbase without left/right, measure either the left or right wheelbase. If the wheelbase is the same on both left and right, the right wheelbase is optional.
  • Track: Distance between front/rear left wheel center and front/rear right wheel center in meters. If asked for just Track without front/rear, measure either the front or rear track.
  • Diameter: Distance between bottom of the front/rear wheel to the top of the front/rear wheel (wheel height) in meters. Note: wheel diameter must include tires as well.

Configure checkerboard and Aruco:

AruCo markers are used for automatic wheel detection. Add the square size of the marker.
Similarly, checkerboard configurations need to be updated
  • Horizontal Corner Count: These are the count of corners in the top row from first to last. (left to right). The blue dot's shown in the above preview correspond to the horizontal corners.
  • Vertical Corner Count: These are the count of corners in the left column from the first to the last. (top to bottom). The red dot's shown in the above preview correspond to the vertical corners.
  • Square Size: It is the length of a square arm in meters. The square size corresponds to the length of the yellow square highlighted in the preview.
  • Left padding: The distance from the leftmost side of the board to the left-most corner point in meters. Corresponds to the blue line in the preview.
  • Right padding: The distance from the rightmost side of the board to the rightmost corner point in meters. Corresponds to the red line in the preview.
  • Top padding: The distance from the topmost side of the board to the topmost corner point in meters. Corresponds to the red line in the preview.
  • Bottom padding: The distance from the bottom-most side of the board to the bottom-most corner point in meters. Corresponds to the blue line in the preview.

Name of the Lidar:

Upload mounted Lidar files:

Upload left and right mounted Lidar files. Left mounted Lidar pcd is recorded when the checkerboard is kept on the left side of the vehicle. Similarly right mounted pcd is recorded when the checkerboard is kept on the right side of the vehicle.
For now, we are supporting only the pcd for the Lidar recordings.

Make sparse board dense:

Users need to select the four border corners of the board. We then identify the edges of the board and also make the spare board dense. Users can select the options shown in the top right corner to display edge points or the checkerboard.
This step has to be repeated for both the point cloud files.

External camera intrinsics:

Users needs to input the intrinsic parameters for the external camera which is used for the calibration.

Upload images for the left-view:

Users need to upload the images taken from the external camera for the left-view of the vehicle.
A minimum of two images is required for the calibration.

Detect target corners:

Checkerboard corners along with the aruco markers attached to the vehicle wheels are detected in this step.

Upload images for right-view:

Users need to upload the images taken from the external camera for the right-view of the vehicle.
A minimum of two images is required for the calibration.

Detect target corners:

Checkerboard corners along with the aruco markers attached to the vehicle wheels are detected in this step.

Run calibrate:

Click on run calibrate to do the calibration. After calibration, this gives us the extrinsic parameters to the right side of the tool.

Visualization:

The visualization shows the fused point cloud along with the vehicle. Users can verify the results visually using this option.