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autoware_camera_lidar_calibrator package from autoware_learn repo

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API Docs
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Package Summary

Tags No category tags.
Version 1.12.0
License Apache 2
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware src learn and recode.
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
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

Autoware CameraLidarCalibration tools, this package includes work from http://www.ros.org/wiki/camera_calibration

Additional Links

No additional links.

Maintainers

  • Abraham Monrroy
  • Jacob Lambert

Authors

  • Jacob Lambert
  • Abraham Monrroy
autoware/utilities/autoware_camera_lidar_calibrator/README.md

Autoware Camera-LiDAR Calibration Package

How to calibrate

Camera-LiDAR calibration is performed in two steps:

  1. Obtain camera intrinsics
  2. Obtain camera-LiDAR extrinsics

Camera intrinsic calibration

The intrinsics are obtained using the autoware_camera_calibration script, which is a fork of the official ROS calibration tool.

How to launch

  1. In a sourced terminal:
    rosrun autoware_camera_lidar_calibrator cameracalibrator.py --square SQUARE_SIZE --size MxN image:=/image_topic
  2. Play a rosbag or stream from a camera in the selected topic name.
  3. Move the checkerboard around within the field of view of the camera until the bars turn green.
  4. Press the CALIBRATE button.
  5. The output and result of the calibration will be shown in the terminal.
  6. Press the SAVE button.
  7. A file will be saved in your home directory with the name YYYYmmdd_HHMM_autoware_camera_calibration.yaml.

This file will contain the intrinsic calibration to rectify the image.

Parameters available

Flag| Parameter| Type| Description| —–|———-|—–|——– –square|SQUARE_SIZE|double |Defines the size of the checkerboard square in meters.| –size|MxN|string |Defines the layout size of the checkerboard (inner size).| image:=|image|string |Topic name of the camera image source topic in raw format (color or b&w).| –min_samples|min_samples|integer |Defines the minimum number of samples required to allow calibration.| –detection|engine|string|Chessboard detection engine, default cv2 or matlab | For extra details please visit: http://www.ros.org/wiki/camera_calibration

Matlab checkerboard detection engine (beta)

This node additionally supports the Matlab engine for chessboard detection, which is faster and more robust than the OpenCV implementation.

  1. Go to the Matlab python setup path /PATH/TO/MATLAB/R201XY/extern/engines/python.
  2. Run python setup.py install to setup Matlab bindings.

To use this engine, add --detection matlab to the list of arguments, i.e.
rosrun autoware_camera_lidar_calibrator cameracalibrator.py --detection matlab --square SQUARE_SIZE --size MxN image:=/image_topic

Calibration

Camera-LiDAR extrinsic calibration

Camera-LiDAR extrinsic calibration is performed by clicking on corresponding points in the image and the point cloud.

This node uses clicked_point and screenpoint from the rviz and image_view2 packages respectively.

How to launch

  1. Perform the intrinsic camera calibration using camera intrinsic calibration tool described above (resulting in the file YYYYmmdd_HHMM_autoware_camera_calibration.yaml).
  2. In a sourced terminal:
    roslaunch autoware_camera_lidar_calibrator camera_lidar_calibration.launch intrinsics_file:=/PATH/TO/YYYYmmdd_HHMM_autoware_camera_calibration.yaml image_src:=/image
  3. An image viewer will be displayed.
  4. Open Rviz and show the point cloud and the correct fixed frame.
  5. Observe the image and the point cloud simultaneously.
  6. Find a point within the image that you can match to a corresponding point within the point cloud.
  7. Click on the pixel of the point in the image.
  8. Click on the corresponding 3D point in Rviz using the Publish Point tool.
  9. Repeat this with at least 9 different points.
  10. Once finished, a file will be saved in your home directory with the name YYYYmmdd_HHMM_autoware_lidar_camera_calibration.yaml.

This file can be used with Autoware’s Calibration Publisher to publish and register the transformation between the LiDAR and camera. The file contains both the intrinsic and extrinsic parameters.

Parameters available

Parameter Type Description  
  image_src string Topic name of the camera image source topic. Default: /image_raw.
  camera_id string If working with more than one camera, set this to the correct camera namespace, i.e. /camera0.
  intrinsics_file string Topic name of the camera image source topic in raw format (color or b&w).
  compressed_stream bool If set to true, a node to convert the image from a compressed stream to an uncompressed one will be launched.

Camera-LiDAR calibration example

To test the calibration results, the generated yaml file can be used in the Calibration Publisher and then the Points Image in the Sensing tab.

Calibration

Notes

This calibration tool assumes that the Velodyne is installed with the default order of axes for the Velodyne sensor.

  • X axis points to the front
  • Y axis points to the left
  • Z axis points upwards
CHANGELOG

Changelog for package autoware_camera_lidar_calibrator

1.11.0 (2019-03-21)

  • [fix] Install commands for all the packages (#1861)
    • Initial fixes to detection, sensing, semantics and utils
    • fixing wrong filename on install command
    • Fixes to install commands
    • Hokuyo fix name
    • Fix obj db
    • Obj db include fixes
    • End of final cleaning sweep
    • Incorrect command order in runtime manager
    • Param tempfile not required by runtime_manager
      • Fixes to runtime manager install commands
    • Remove devel directory from catkin, if any
    • Updated launch files for robosense
    • Updated robosense
    • Fix/add missing install (#1977)
    • Added launch install to lidar_kf_contour_track
    • Added install to op_global_planner
    • Added install to way_planner
    • Added install to op_local_planner
    • Added install to op_simulation_package
    • Added install to op_utilities
    • Added install to sync
      • Improved installation script for pointgrey packages
    • Fixed nodelet error for gmsl cameras
    • USe install space in catkin as well
    • add install to catkin
    • Fix install directives (#1990)
    • Fixed installation path
    • Fixed params installation path
    • Fixed cfg installation path
    • Delete cache on colcon_release
  • Fix package name and dependency (#1914)
  • Fix license notice in corresponding package.xml
  • Contributors: Abraham Monrroy Cano, Akihito Ohsato, amc-nu

1.10.0 (2019-01-17)

  • Fixes for catkin_make
  • Switch to Apache 2 license (develop branch) (#1741)
    • Switch to Apache 2

    * Replace BSD-3 license header with Apache 2 and reassign copyright to the Autoware Foundation.

    • Update license on Python files
    • Update copyright years
    • Add #ifndef/define _POINTS_IMAGE_H_
    • Updated license comment
  • Use colcon as the build tool (#1704)
    • Switch to colcon as the build tool instead of catkin
    • Added cmake-target
    • Added note about the second colcon call
    • Added warning about catkin* scripts being deprecated
    • Fix COLCON_OPTS
    • Added install targets
    • Update Docker image tags
    • Message packages fixes
    • Fix missing dependency
  • Feature/perception visualization cleanup (#1648)
      • Initial commit for visualization package
    • Removal of all visualization messages from perception nodes
    • Visualization dependency removal
    • Launch file modification
      • Fixes to visualization
    • Error on Clustering CPU
    • Reduce verbosity on markers
    • intial commit
      • Changed to 2 spaces indentation
    • Added README
    • Fixed README messages type
    • 2 space indenting
    • ros clang format
    • Publish acceleration and velocity from ukf tracker
    • Remove hardcoded path
    • Updated README
    • updated prototype
    • Prototype update for header and usage
    • Removed unknown label from being reported
    • Updated publishing orientation to match develop
      • Published all the trackers
    • Added valid field for visualization and future compatibility with ADAS ROI filtering
    • Add simple functions
    • Refacor code
      • Reversed back UKF node to develop
    • Formatted speed
    • Refactor codes
    • Refactor codes
    • Refactor codes
    • Refacor codes
    • Make tracking visualization work
    • Relay class info in tracker node
    • Remove dependency to jskbbox and rosmarker in ukf tracker
    • apply rosclang to ukf tracker
    • Refactor codes
    • Refactor codes
    • add comment
    • refactor codes

    * Revert "Refactor codes" This reverts commit 135aaac46e49cb18d9b76611576747efab3caf9c. * Revert "apply rosclang to ukf tracker" This reverts commit 4f8d1cb5c8263a491f92ae5321e5080cb34b7b9c. * Revert "Remove dependency to jskbbox and rosmarker in ukf tracker" This reverts commit 4fa1dd40ba58065f7afacc5e478001078925b27d. * Revert "Relay class info in tracker node" This reverts commit 1637baac44c8d3d414cc069f3af12a79770439ae.

    • delete dependency to jsk and remove pointcloud_frame
    • get direction nis
    • set velocity_reliable true in tracker node
    • Add divided function
    • add function
    • Sanity checks
    • Relay all the data from input DetectedObject
    • Divided function work both for immukf and sukf
    • Add comment
    • Refactor codes
    • Pass immukf test
    • make direction assisted tracking work
    • Visualization fixes
    • Refacor codes
    • Refactor codes
    • Refactor codes
    • refactor codes
    • refactor codes
    • Refactor codes
    • refactor codes
    • Tracker Merging step added
    • Added launch file support for merging phase
    • lane assisted with sukf
    • Refactor codes
    • Refactor codes
      • change only static objects
    • keep label of the oldest tracker
    • Static Object discrimination
    • Non rotating bouding box
    • no disappear if detector works
    • Modify removeRedundant a bit
    • Replacement of JSK visualization for RViz Native Markers
    • Added Models namespace to visualization
    • Naming change for matching the perception component graph
      • Added 3D Models for different classes in visualization
    • 2D Rect node visualize_rects added to visualization_package
  • Fix/intrinsic calibration opencv check (#1696)
    • Removed python yaml dependency that was causing issues. Tested on kinetic/opencv3.3
    • bug fix: error unpacking opencv version if not minor version
  • Fix Ros/ROS naming convention
  • Contributors: Abraham Monrroy Cano, Esteve Fernandez, Jacob Lambert, amc-nu

1.9.1 (2018-11-06)

1.9.0 (2018-10-31)

  • [fix] Added option to publish to specific camera frame on camera publisher (#1565)
      • Added option to publish to specific camera frame on camera publisher
    • fixes to the node
    • Added New line to UI on each param.
      • Updates to launch files using calibration publisher
    • Updated naming after develop merge
    • Updated suscription type to topic for calibration publisher
  • [fix]Removed python yaml dependency that was causing issues. Tested on kinetic/opencv3.3 (#1622)
  • Fix/intrinsic calibration gui aa (#1581)
    • Fixed calibration UI text anti-aliasing in CV3
    • tested on cv2 and cv3 (indigo and kinetic)
  • Contributors: Abraham Monrroy Cano, Jacob Lambert

1.8.0 (2018-08-31)

  • [Fix] Moved C++11 flag to autoware_build_flags (#1395)
  • [Feature] Makes sure that all binaries have their dependencies linked (#1385)
  • [Fix] Extend and Update interface.yaml (#1291)
  • Contributors: Esteve Fernandez, Kenji Funaoka

1.7.0 (2018-05-16)

  • update Version from 1.6.3 to 1.7.0 in package.xml and CHANGELOG.rst
  • Modify package xml version other than 1.6.3
  • Remove history of sub-branches
  • Add automatically-generated CHANGELOG.rst
  • Fix/cmake cleanup (#1156)
    • Initial Cleanup
    • fixed also for indigo
    • kf cjeck
    • Fix road wizard
    • Added travis ci
    • Trigger CI
    • Fixes to cv_tracker and lidar_tracker cmake
    • Fix kitti player dependencies
    • Removed unnecessary dependencies
    • messages fixing for can
    • Update build script travis
    • Travis Path
    • Travis Paths fix
    • Travis test
    • Eigen checks
    • removed unnecessary dependencies
    • Eigen Detection
    • Job number reduced
    • Eigen3 more fixes
    • More Eigen3
    • Even more Eigen
    • find package cmake modules included
    • More fixes to cmake modules
    • Removed non ros dependency
    • Enable industrial_ci for indidog and kinetic
    • Wrong install command
    • fix rviz_plugin install
    • FastVirtualScan fix
    • Fix Qt5 Fastvirtualscan
    • Fixed qt5 system dependencies for rosdep
    • NDT TKU Fix catkin not pacakged
    • Fixes from industrial_ci
  • [fix] Added missing Qt5Core dependency for PCL in autoware_calibration package (#1149)
    • Added missing Qt5Core dependency for PCL
    • Removed unnecessary library linking
  • Output file updated
  • fixed matlab chessboard detection
  • Initial Release Autoware Camera-LiDAR calibration tool (#1131)
    • Initial Release Autoware Camera-LiDAR calibration tool

    * Update README File is saved now

    • Editorial changes to readme file.
  • Contributors: AMC, Abraham Monrroy, Jacob Lambert, Kenji Funaoka, Kosuke Murakami

1.6.3 (2018-03-06)

1.6.2 (2018-02-27)

1.6.1 (2018-01-20)

1.6.0 (2017-12-11)

1.5.1 (2017-09-25)

1.5.0 (2017-09-21)

1.4.0 (2017-08-04)

1.3.1 (2017-07-16)

1.3.0 (2017-07-14)

1.2.0 (2017-06-07)

1.1.2 (2017-02-27 23:10)

1.1.1 (2017-02-27 22:25)

1.1.0 (2017-02-24)

1.0.1 (2017-01-14)

1.0.0 (2016-12-22)

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.

Launch files

  • launch/camera_lidar_calibration.launch
    • roslaunch autoware_camera_lidar_calibrator camera_lidar_calibration.launch intrinsics_file:=/home/ne0/Desktop/calib_heat_camera1_rear_center_fisheye.yaml compressed_stream:=True camera_id:=camera1
      • image_src [default: /image_raw]
      • camera_info_src [default: /camera_info]
      • camera_id [default: /]
      • intrinsics_file
      • compressed_stream [default: false]
      • target_frame [default: velodyne]
      • camera_frame [default: camera]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_camera_lidar_calibrator at Robotics Stack Exchange

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