Multi-LiDAR Calibration

Overview: Deepen Calibrate is a software tool that makes the critical task of sensor data calibration simple and quick.

1. Calibrations:

  • This page allows the users to create, list, launch and delete calibration datasets. Admins can manage user’s access to these datasets on this page.

  • Click on ‘New Calibration’ to create a new calibration dataset.

2. Calibration Selection:

  • Upon clicking the ‘New Calibration’ button, the user can make a selection from the different calibrations. Select ‘Multi-LiDAR Calibration’ to create a new multi-LiDAR calibration dataset.

3. Calibration Instructions Page:

  • Upon selecting ‘Multi-LiDAR Calibration’, the user is welcomed to the instructions page

  • Click on ‘Get started’ after finishing with the instructions. The user must provide a name for the calibration dataset and click on ‘Set details’ to proceed ahead.

4. Calibration Pipeline:

Multi-LiDAR Calibration consists of four stages:

  • Setup details: Add details for your LiDAR sensors.

  • Add files: Upload a single pcd file for each LiDAR sensor.

  • Mapping: Map the uploaded frames by picking exactly four points from each frame.

  • Calibrate: Run the calibration algorithm of your choice and visualise the results.

A few other details :

  1. The user can choose to hit the ‘Save changes’ option at any stage to prevent loss of work.

  2. The user can navigate between the stages and update the details as per convenience.

  3. Download the results by using the ‘Export’ option.

  4. Click on the ‘Help Center’ button ( the top right corner) to get your doubts answered related to the calibration.

4.1 Setup Details:

The user can fill in the basic details related to each LiDAR sensor on this page. Click on ‘Continue’ to proceed to the ‘Add Files’ stage.

4.2 Add files:

Upload a single file(.pcd format only) for each of the two LiDAR sensors and click on ‘Continue’ to proceed to the ‘Mapping’ stage.

Note: File name should NOT contain any whitespaces.

4.3 Mapping:

Mapping point clouds helps to determine where a point present in a frame from LiDAR 1 correlates to points in the frame from LiDAR 2. To proceed to calibration, our algorithm requires mapping exactly four points to get accurate results.

The different interactions with the point clouds are::

  • Add marker: enable brush.

  • Erase marker: enable eraser.

  • Clear markers: clear all the points selection.

  • Toolbar: allows rotate, pan, zoom in/out operations.

How to map point clouds using markers?

To start mapping the point clouds:

  1. Click the ‘Add Marker’ button, and click in the area of interest for LiDAR 1.

  2. Map the exact points for LiDAR 2 by adding a marker.

  3. Repeat the steps for all 4 markers.

To remove a misplaced marker, click the ‘Erase Marker’ button and click on the incorrect marker. To remove all the added markers, click on the ‘Clear Markers’ button.

After mapping all the four markers in both the frames, we get quick estimated calibration results. Validate the results in Visualize mode before proceeding to final calibration as these estimates are used to calculate the final extrinsic parameters.

After validating the estimated calibration results, click on Continue to move to the Calibrate stage. If the calibration results seem quite off, then one can use clear markers to clear all markers or Erase marker to erase a specific marker. And retry to correspondence four markers from both lidars.

4.4 Calibrate:

Calibrate your LiDAR sensors by using Generalized Iterative Closest Point(GICP) or Normal Distributions Transform(NDT) algorithm. To find which one to use for your LiDAR sensors, please look in the ‘Help Center’ section.

Click on GICP or NDT to fetch respective extrinsic parameters. ​​This may take up to 2-3 minutes for us to get more accurate results, depending on the quality of point cloud files.

Validate the results in Visualize mode and mark the calibration process is complete. These extrinsic parameters can be exported by using the ‘Export’ option.

Please note that :

  1. The error rate displayed for each algorithm represents the fitness score.

  2. We provide a default value for voxel size in the case of the NDT algorithm based on heuristics. The user can wish to choose another value.

5. Extrinsic Calibration Output:

  • roll, pitch, yaw, px, py, pz are the extrinsic parameters downloaded from the calibration tool.

  • lidar1Point is the 3d coordinates of a point in the lidar1 coordinate system.

  • lidar2Point is the 3d coordinates of a point in the lidar2 coordinate system.