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lidar_camera_calib package from lidar_camera_calib repolidar_camera_calib |
Package Summary
| Tags | No category tags. |
| Version | 1.0.0 |
| License | TODO |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | A extrinsic calibration tool between LiDAR and camera in targetless environment, based off https://github.com/hku-mars/livox_camera_calib |
| Checkout URI | https://github.com/simi-asher/lidar_camera_calib.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-01-03 |
| Dev Status | UNKNOWN |
| CI status | No Continuous Integration |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
The lidar_camera_calib package
Additional Links
No additional links.
Maintainers
- vpatil
Authors
No additional authors.
lidar_camera_calib
lidar_camera_calib is a tool that extends Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments to spinning LiDARs (e.g. Velodyne, Ouster).
The original tool is a robust, high accuracy extrinsic calibration tool LiDAR-camera calibration in a targetless environment. The algorithm can run in both indoor and outdoor settings, and only requires edge information in the scene. If the scene is suitable, we can achieve pixel-level accuracy similar to or even beyond the target based method.
<img src="pics/color_cloud.png" width = 100% >
<font color=#a0a0a0 size=2>An example of a outdoor calibration scenario. We color the point cloud with the calibrated extrinsic and compare with actual image. A and C are locally enlarged
views of the point cloud. B and D are parts of the camera image
corresponding to point cloud in A and C.</font>
Key features:
- Extends an automatic targetless extrinsic calibration tool for LiDAR-Camera Calibration to spinning LiDARs as well. It has been tested in both indoor and outdoor environments and algorithm is able to converge and have good accuracy.
- Supports ROS2 (has been tested with ROS2 Humble).
Results:
Indoor results:
<img src="pics/result1.png" width = 100% >
<font color=#a0a0a0 size=2>Coloured pointcloud after calibration of a portion of a corridor of the Field Robotics Center
</font>
<img src="pics/result2.png" width = 100% >
<font color=#a0a0a0 size=2>Coloured pointcloud after calibration of a closed hallway
</font>
Outdoor results:
<img src="pics/outdoor-img1.png" width = 100% >
<img src="pics/outdoor-result1.png" width = 100% >
<font color=#a0a0a0 size=2>Coloured pointcloud after calibration outside Newell-Simon Hall
</font>
1. Prerequisites
1.1 Ubuntu and ROS2
Ubuntu 64-bit 22.04. ROS2 Humble and additional ROS package:
sudo apt-get install ros-XXX-cv-bridge ros-xxx-pcl-conversions
rosdep install --from-paths ./src --ignore-packages-from-source --rosdistro humble -y
1.2 Eigen
Follow Eigen Installation
1.3 Ceres Solver
Follow Ceres Installation.
1.4 PCL
Follow PCL Installation. (Our code is tested with PCL1.12)
2. Usage:
- Record a ROS2 bag file while moving the LiDAR-camera setup. During our testing, we tried both lateral translation and pitching motion and both yielded good convergence, although pitching will give you a denser pointcloud.
- Clone, build and run lidarslam_ros2 on this bag file and generate a PCD file. You can apply this patch to run with our example bag files.
- Extract the first image from the recorded camera data in this bag file and save it. You can use the given extract_image_from_bag.py script for this.
- Modify the calib.yaml, change the data path to your local data path and provide the instrinsic matrix and distor coeffs for your camera. Run the package as
ros2 launch lidar_camera_calib calib.launch.py
3. Example data
You can find ROS2 bags and PCD and image files that we have collected here
CHANGELOG
No CHANGELOG found.
Wiki Tutorials
This package does not provide any links to tutorials in it's rosindex metadata.
You can check on the ROS Wiki Tutorials page for the package.
Package Dependencies
| Deps | Name |
|---|---|
| ament_cmake | |
| cv_bridge | |
| rclcpp | |
| rclpy | |
| sensor_msgs | |
| std_msgs |
System Dependencies
| Name |
|---|
| libpcl-all-dev |
Dependant Packages
No known dependants.
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
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