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thermal range extrinsic calibration

gazebo simulation

You can find the simulation environment in this repo

experiment

thermal_range_calib

thermal_range_calib is a robust, high-accuracy extrinsic calibration tool between thermal camera LiDAR (e.g. Livox) and RGBD-camera in targetless environment. If the scene is suitable, we can achieve high-level accuracy similar to the target-based method.

The system architecture is shown in the following diagram:

6971701232187_ pic

Related paper

Related paper is coming soon...

1. Prerequisites

1.1 Ubuntu and ROS

Ubuntu 64-bit 16.04 or 18.04. ROS Kinetic or Melodic. ROS Installation and its additional ROS pacakge:

    sudo apt-get install ros-XXX-cv-bridge ros-xxx-pcl-conversions

1.2 Eigen

Follow Eigen Installation

1.3 Ceres Solver 1.14.0

Download Ceres 1.14.0 from here Follow Ceres Installation.

1.4 PCL

Follow PCL Installation. (Our code is tested with PCL1.7)

2. Build

Clone the repository and catkin_make:

cd ~/catkin_ws/src
git clone https://github.com/allenthreee/thermal_range_calib.git
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash

3. Run our example

our thermal camera intrinsic is shown below:

thermal_camera_intrinsics_fx_fy_00

thermal_camera_intrinsics_cx_cy_00

example data could be download here: google drive

Move it to your local path, and then change the file path in thermal_calib.yaml to your data path. Then directly run

roslaunch thermal_range_calib thermal_calib.launch

Following are some fusion examples:

6951701231997_ pic

6961701231999_ pic

4. Run on your own sensor set

4.1 Record data

Record thermal image files to png format and the point cloud to pcd files(you can record it from the simulation or hardware).

4.2 Modify the calib.yaml

Change the data path to your local data path.
Provide the instrinsic matrix and distor coeffs for your thermal camera.

5. Acknowledgements

Thanks for Livox_Camera_calib(C. Yuan et al. Pixel-level extrinsic self calibration of high resolution lidar and camera in targetless environments).