U2UData：面向集群无人机自主飞行的大规模协同感知数据集
U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs Autonomous Flight
AI总结：
本文提出了首个面向集群无人机自主飞行的大规模协同感知数据集U2UData，基于真实世界映射的仿真环境U2USim构建，包含多传感器数据与环境参数，并引入协同3D检测与跟踪任务及全面基准测试。
摘要：
现代自主飞行感知系统对遮挡敏感且远程能力有限，这是提升低空经济任务性能的关键瓶颈。近期研究表明，无人机间（U2U）协同感知系统具有颠覆自主飞行产业的巨大潜力。然而，缺乏大规模数据集阻碍了该领域的进展。本文提出了U2UData，这是首个面向集群无人机自主飞行的大规模协同感知数据集。该数据集由三架在U2USim中自主飞行的无人机采集，覆盖9平方公里的飞行区域。它包含315K帧LiDAR数据、945K帧RGB和深度图像，以及针对3个类别的2.41M个标注3D边界框。此外，还包含覆盖所有飞行路线的亮度、温度、湿度、烟雾和气流数值。U2USim是首个真实世界映射的集群无人机仿真环境，以云南省为原型，包含4种地形、7种天气条件和8种传感器类型。U2UData引入了两项感知任务：协同3D目标检测与协同3D目标跟踪。本文提供了最新协同感知算法在这些任务上的全面基准测试。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
