Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged direct_visual_lidar_calibration at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | AMENT_CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Description | |
| Checkout URI | https://github.com/ieiauto/autodrrt.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2025-09-29 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- k.koide
Authors
direct_visual_lidar_calibration
This package provides a toolbox for LiDAR-camera calibration that is:
- Generalizable: It can handle various LiDAR and camera projection models including spinning and non-repetitive scan LiDARs, and pinhole, fisheye, and omnidirectional projection cameras.
- Target-less: It does not require a calibration target but uses the environment structure and texture for calibration.
- Single-shot: At a minimum, only one pairing of a LiDAR point cloud and a camera image is required for calibration. Optionally, multiple LiDAR-camera data pairs can be used for improving the accuracy.
- Automatic: The calibration process is automatic and does not require an initial guess.
- Accurate and robust: It employs a pixel-level direct LiDAR-camera registration algorithm that is more robust and accurate compared to edge-based indirect LiDAR-camera registration.
Documentation: https://koide3.github.io/direct_visual_lidar_calibration/
Docker hub: koide3/direct_visual_lidar_calibration

Dependencies
Getting started
License
This package is released under the MIT license.
Publication
Koide et al., General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox, ICRA2023, [PDF]
Contact
Kenji Koide, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Package Dependencies
| Deps | Name |
|---|---|
| catkin | |
| ament_cmake | |
| ament_cmake_python | |
| roscpp | |
| rosbag | |
| rclcpp | |
| rosbag2_cpp | |
| cv_bridge | |
| pcl_ros | |
| sensor_msgs |
System Dependencies
| Name |
|---|
| fmt |