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https://github.com/alibaba/multiple-cameras-and-3D-LiDARs-extrinsic-calibration

This repo contains source code of our paper presented in IROS2021 "Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs"
https://github.com/alibaba/multiple-cameras-and-3D-LiDARs-extrinsic-calibration

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This repo contains source code of our paper presented in IROS2021 "Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs"

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# Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs



## Updates



* [2021/09/01] first commit, source code of localization and calibration stage; Given sparse map of panoramic infrastructure, we can easily calibrate the extrinsics among multi-camera and multi-LiDAR. In order to facilitate camera intrinsic calibration and imu calibration, [Kalibr toolbox](https://github.com/ethz-asl/kalibr) is used in our scripts, and [imu_utils](https://github.com/gaowenliang/imu_utils) code is  simplified in our source code. 

* [2021/10/01] source code of panoramic infrastructure reconstruction; coming soon...



## Introduction



 This paper is accpeted in 2021 IROS, the preprint version is accessible in [arXiv](https://arxiv.org/abs/2103.12941).  In this paper, we propose a single-shot solution for calibrating extrinsic transformations among multiple cameras and 3D LiDARs. We establish a panoramic infrastructure, in which a camera or LiDAR can be robustly localized using data from single frame. Experiments are conducted on three devices with different camera-LiDAR configurations, showing that our approach achieved comparable calibration accuracy with the state-of-the-art approaches but with much greater efficiency.



![image-20210724161755730](./assets/image-20210724161755730.png)



## Prerequisities

1. **Kalibr**



   Follow  [Kalibr installation](https://github.com/ethz-asl/kalibr/wiki/installation).



2. **Ceres**



   follow [ceres installation](http://ceres-solver.org/installation.html).



3. **CCTag**



   Follow [cctag installation](https://github.com/fangchuan/CCTag/blob/develop/INSTALL.md).



4. **Yaml-cpp**(>=0.6.0)



   Follow [yaml-cpp installation](https://github.com/jbeder/yaml-cpp#how-to-build).



5. **Boost**(>=1.69)



   Follow [boost installation](https://www.boost.org/doc/libs/1_76_0/more/getting_started/unix-variants.html#id26).



6. **Open3D**(>=0.10)



   follow [open3d installation](http://www.open3d.org/docs/release/compilation.html#ubuntu-macos).



## Docker Support



To further facilitate the building process, we add docker in our code. Docker environment is like a sandbox, thus makes our code environment-independent.



Docker build:



```bash

docker/build

```



We have built a public docker image beforehand, please download the [archived file](https://drive.google.com/file/d/1WqkYovHSsb4BI_V_soT5umzXNUleR3RB/view?usp=share_link) if you need.



Run docker with our test data, please refer to [docker_usage_en.md](./docker_usage_en.md).



## Quick Start



1. Build the source code in **Ubuntu 16.04**/**Ubuntu 18.04**:

  

   ```bash

   git clone https://github.com/alibaba/multiple-cameras-and-3D-LiDARs-extrinsic-calibration.git

   cd multiple-cameras-and-3D-LiDARs-extrinsic-calibration

   mkdir build && cd build

   cmake ..

   make -j8

   ```

   

2. Download the [test data](https://drive.google.com/file/d/1Cv0FGCFS3pz7H1yHeFi5lkA2ZzCAYpYk/view?usp=share_link).



3. Build the source code in docker, refer to [docker_useage_en.md](./docker_usage_en.md) for further tutorial.



## Citation



If you find this code is useful in your research, please cite:



```

@article{fang2021single,

  title={Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs},

  author={Fang, Chuan and Ding, Shuai and Dong, Zilong and Li, Honghua and Zhu, Siyu and Tan, Ping},

  journal={arXiv preprint arXiv:2103.12941},

  year={2021}

}

```



## Acknowledgements



Thanks to gaowenliang for opening source of his excellent works  [imu_utils](https://github.com/gaowenliang/imu_utils). Thanks to the maintenance team of Kalibr for the well-known open-source project [Kalibr](https://github.com/ethz-asl/kalibr).



## License

The source code is released under MIT license.



We are still working on improving the performance and reliability of our codes. For any technical issues, please contact me via email .