U2UData+：面向具身长程任务的可扩展集群无人机自主飞行数据集
U2UData+: A Scalable Swarm UAVs Autonomous Flight Dataset for Embodied Long-horizon Tasks
AI总结：
针对现有数据集无法支撑集群无人机完成具身长程（ELH）任务的问题，本文提出大规模集群无人机自主飞行数据集U2UData+及配套可扩展闭环验证平台，提供野生动物保护ELH任务基准。
摘要：
面向具身长程（Embodied Long-Horizon, ELH）任务的集群无人机自主飞行对推动低空经济发展至关重要。但受数据集限制，现有方法仅聚焦特定基础任务，无法在真实场景中部署完成ELH任务。ELH任务并非基础任务的简单拼接，需要处理长程依赖、维持具身持久状态并适配动态目标变化。本文提出U2UData+，这是首个面向ELH任务的大规模集群无人机自主飞行数据集，也是首个可扩展的集群无人机数据在线采集与算法闭环验证平台。该数据集由15架无人机在执行ELH任务的自主协同飞行中采集，包含12个场景、720条轨迹、120小时数据，单条轨迹时长600秒，含432万帧激光雷达（LiDAR）数据、1296万帧RGB图像，还覆盖所有飞行航线的亮度、温度、湿度、烟雾、气流数值。该平台支持自定义仿真器、无人机、传感器、飞行算法、编队模式与ELH任务，用户可通过可视化控制窗口在线一键部署采集自定义数据集，并通过闭环仿真验证算法。U2UData+还引入了面向野生动物保护的ELH任务，提供了包含9个SOTA模型的全面基准，项目地址为https://fengtt42.github.io/U2UData-2/。
英文摘要：
Swarm UAV autonomous flight for Embodied Long-Horizon (ELH) tasks is crucial for advancing the low-altitude economy. However, existing methods focus only on specific basic tasks due to dataset limitations, failing in real-world deployment for ELH tasks. ELH tasks are not mere concatenations of basic tasks, requiring handling long-term dependencies, maintaining embodied persistent states, and adapting to dynamic goal shifts. This paper presents U2UData+, the first large-scale swarm UAV autonomous flight dataset for ELH tasks and the first scalable swarm UAV data online collection and algorithm closed-loop verification platform. The dataset is captured by 15 UAVs in autonomous collaborative flights for ELH tasks, comprising 12 scenes, 720 traces, 120 hours, 600 seconds per trajectory, 4.32M LiDAR frames, and 12.96M RGB frames. This dataset also includes brightness, temperature, humidity, smoke, and airflow values covering all flight routes. The platform supports the customization of simulators, UAVs, sensors, flight algorithms, formation modes, and ELH tasks. Through a visual control window, this platform allows users to collect customized datasets through one-click deployment online and to verify algorithms by closed-loop simulation. U2UData+ also introduces an ELH task for wildlife conservation and provides comprehensive benchmarks with 9 SOTA models. U2UData+ can be found at https://fengtt42.github.io/U2UData-2/.
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。
