arXiv:2509.00055cs.ROcs.AI2025-09AAAI被引 6

首个面向长时序任务的规模化无人机群自主飞行数据集,支持在线采集与算法闭环验证。

U2UData+: A Scalable Swarm UAVs Autonomous Flight Dataset for Embodied Long-horizon Tasks

  • 构建可扩展的无人机群协同飞行数据平台,支持在线一键采集与算法闭环测试。
  • 包含15架无人机、12个场景、720条轨迹、共120小时飞行数据,每条轨迹600秒,含432万帧点云和1296万帧图像。
  • 首次为野生动物保护设计长时序任务,提供9种先进模型基准,适合研究群体智能与真实场景部署。

无人机群在低空经济中的长时序具身任务(ELH)自主飞行至关重要,但现有方法受限于数据集,仅能处理基础任务,难以实现真实场景部署。ELH任务并非基础任务的简单拼接,需应对长期依赖、持续状态维持及动态目标变化。本文提出U2UData+,首个面向ELH任务的大规模无人机群自主飞行数据集,也是首个支持数据在线采集与算法闭环验证的可扩展平台。数据由15架无人机在自主协同飞行中采集,涵盖12个场景、720条轨迹、总时长120小时,每条轨迹600秒,含432万帧激光雷达数据和1296万帧RGB图像,并记录所有航路的亮度、温度、湿度、烟雾和气流信息。平台支持模拟器、无人机、传感器、飞行算法、编队模式及任务的自定义配置,通过可视化控制界面可一键部署在线采集或进行闭环仿真验证。此外,平台引入野生动物保护领域的新型ELH任务,提供9个当前最优模型的全面评测基准。项目主页:https://fengtt42.github.io/U2UData-2/

原文摘要 · Abstract (English)

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/.

无人机群长时序任务数据集闭环验证

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