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 and the project page
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 teh Calibration rosbag in 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
The code has been tested on Ubuntu 20.04 with ROS Noetic
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PCL
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Eigen
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Livox_ros_driver, Follow livox_ros_driver Installation.
cd ~/catkin_ws/src
git clone https://github.com/TIERS/multi_lidar_multi_uav_dataset
cd ..
catkin build
If you use this dataset for any academic work, please cite the following publication:
@misc{catalano2023towards,
title={Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset},
author={Iacopo Catalano and Xianjia Yu and Jorge Pena Queralta},
year={2023},
eprint={},
archivePrefix={arXiv},
primaryClass={cs.RO}
}