Data Collection for Multi Target Lidar-Camera Calibration
Last updated
Last updated
Charucoboard is the calibration target. Charucoboard of the following dictionaries of any size and squares can be used as the target. Targets should be as flat as possible and the surface of the target should be anti-glare (matte finish)
for supported charuco dictionaries.
Note: When multiple targets are used, make sure targets are of different dictionaries.
We suggest that users make at least 1.0m*1.0m charcoboards for good corner detection.
Place the targets in the focus of the camera and the LiDAR's field of view. The targets should be placed on the ground or on a stand. Avoid holding the targets with your hands.
The targets and all sensors should be static while collecting the data. To avoid time-synchronization problems, please keep the boards and the sensors stationary for at least 10 seconds while collecting each calibration data set.
For example, these are the steps to collect one set of calibration data:
Orient the camera toward the targets. Start recording. Wait for 10 seconds (Don't move/rotate your car/robot/sensors). Stop recording. You must have a recording of images and lidar data for 10 seconds. Extract one image from the camera and one frame of lidar data captured 5 seconds after the recording has started (e.g., if you start recording at 3:00:00, you stop recording at 3:00:10. We need a frame captured at 3:00:05) and save them.
Change the targets' location and orientation. Start recording. Wait 10 seconds (Don't move/rotate your car/robot). Stop recording. Again, you must have a recording of images and lidar data for 10 seconds. Extract one image from the camera and one frame of lidar data captured 5 seconds after the recording starts and save them. (Dataset front_2)
In the same manner, save Dataset front_3, front_4, and front_5.
Multi-target LiDAR Camera calibration works even with a single pair of images and a lidar frame. The more pairs, the better the accuracy will be.
The target is placed on the ground (touching the ground). In such a case, enable the on ground flag in the configuration page. Also, make sure that the lidar data captures the ground points. By doing so, we can optimize the extrinsic parameters using the ground points.
A holder holds the target up in the air and tilts right by around 45 degrees. In such a case, enable the Tilted flag in the target configuration. This approach enables deep optimization, and the extrinsic parameters are further optimized using the edge points of the board.
