https://tiers.github.io/multi_lidar_multi_uav_dataset/

https://tiers.github.io/multi_lidar_multi_uav_dataset/

Last synced: 3 months ago
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• Host: GitHub
• URL: https://tiers.github.io/multi_lidar_multi_uav_dataset/
• Owner: TIERS
• License: mit
• Created: 2023-07-28T07:24:35.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-03T18:31:13.000Z (11 months ago)
• Last Synced: 2024-07-31T02:34:54.451Z (4 months ago)
• Language: C++
• Size: 10.7 MB
• Stars: 48
• Watchers: 0
• Forks: 5
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• Awesome-3D-LiDAR-Datasets - A Multi-LiDAR Multi-UAV Dataset - 64|1x Livox Mid, 1x Livox 360|Odom|Small| (Summary Table / Update: 2023-07-12)

README

        


    
Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset

    

    

    

    

    


    


    Project Page

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    Paper

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    Contact Us

  


  


  


    

  




We present a novel multi-LiDAR dataset specifically designed for UAV tracking. Our dataset includes data from a spinning LiDAR, two solid-state LiDARs with different Field of View (FoV) and scan patterns, and an RGB-D camera. This diverse sensor suite allows for research on new challenges in the field, including limited FoV adaptability and multi-modality data processing. For a comprehensive list of sequences refer to the paper [Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset](https://arxiv.org/abs/2310.09165) and the [project page](https://tiers.github.io/multi_lidar_multi_uav_dataset ) 



## Calibration 

We provide a ROS package to compute the extrinsic parameters between LiDARs and camera based on GICP. As the OS1 has the largest FOV, it is treated as base reference frame ("base_link") in which all the other point clouds are transformed. For the Avia, Mid-360 and Realsense D435, we integrated the first five frames to increase point cloud density.

To use this package, play the Calibration rosbag from our dataset:

~~~

rosbag play Calibration.bag -l

~~~

Then run our calibration launch file:

~~~

roslaunch multi_lidar_multi_uav_dataset lidars_extrinsic_computation.launch

~~~

The computed extrinsic parameters will appear in the terminal:

~~~

OS -> base_link 0 0 0 0 0 0 /os_sensor /base_link 10

Avia -> base_link   0.149354  0.0423582 -0.0524961  3.13419 -3.13908 -3.13281 /avia_frame /base_link 10

Mid360 -> base_link   0.125546 -0.0554536   -0.20206 0.00467344  0.0270294  0.0494959 /mid360_frame /base_link 10

Camera -> base_link -0.172863   0.11895 -0.101785 1.55222 3.11188 1.60982 /camera_depth_optical_frame /base_link 10

~~~

## Install

The code has been tested on Ubuntu 20.04 with ROS Noetic

### Dependencies

- PCL

- Eigen

- Livox_ros_driver, Follow [livox_ros_driver Installation](https://github.com/Livox-SDK/livox_ros_driver).

### Build

```

  cd ~/catkin_ws/src

  git clone https://github.com/TIERS/multi_lidar_multi_uav_dataset 

  cd ..

  catkin build

```

## Citation

If you use this dataset for any academic work, please cite the following publication:

```

@inproceedings{catalano2023towards,

  title={Towards robust uav tracking in gnss-denied environments: a multi-lidar multi-uav dataset},

  author={Catalano, Iacopo and Yu, Xianjia and Queralta, Jorge Pe{\~n}a},

  booktitle={2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)},

  pages={1--7},

  year={2023},

  organization={IEEE}

}

```