U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs Autonomous Flight
<|reference_start|>U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs Autonomous Flight: Modern perception systems for autonomous flight are sensitive to occlusion and have limited long-range capability, which is a key bottleneck in improving low-altitude economic task performance. Recent research has shown that the UAV-to-UAV (U2U) cooperative perception system has great potential to revolutionize the autonomous flight industry. However, the lack of a large-scale dataset is hindering progress in this area. This paper presents U2UData, the first large-scale cooperative perception dataset for swarm UAVs autonomous flight. The dataset was collected by three UAVs flying autonomously in the U2USim, covering a 9 km$^2$ flight area. It comprises 315K LiDAR frames, 945K RGB and depth frames, and 2.41M annotated 3D bounding boxes for 3 classes. It also includes brightness, temperature, humidity, smoke, and airflow values covering all flight routes. U2USim is the first real-world mapping swarm UAVs simulation environment. It takes Yunnan Province as the prototype and includes 4 terrains, 7 weather conditions, and 8 sensor types. U2UData introduces two perception tasks: cooperative 3D object detection and cooperative 3D object tracking. This paper provides comprehensive benchmarks of recent cooperative perception algorithms on these tasks.<|reference_end|>
@article{feng2024u2udata:,
    title={U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs
  Autonomous Flight},
    author={Tongtong Feng, Xin Wang, Feilin Han, Leping Zhang, Wenwu Zhu},
    journal={arXiv preprint arXiv:2408.00606},
    year={2024},
    doi={10.1145/3664647.3681151},
    archivePrefix={arXiv},
    eprint={2408.00606},
    primaryClass={cs.RO}
}