arXiv:2505.23457cs.ROcs.SY2025-05被引 7

无人机+地面车组合系统,实现无卫星信号环境下的长时间自主巡检。

Long Duration Inspection of GNSS-Denied Environments with a Tethered UAV-UGV Marsupial System

  • 用缆绳连接无人机与带电池的地面车,持续供电延长飞行时间。
  • 在无卫星信号环境下完成三轮自动巡检,定位与轨迹跟踪稳定可靠。
  • 开源软硬件设计,实验数据公开,适合机器人巡检研究者参考。

无人机因机动性强,常用于难以到达区域的巡检与应急任务,但其续航受限。本文提出一种由无人机与无人地面车组成的系绳式母体机器人系统,专为全球导航卫星系统(GNSS)拒止环境中的自主长时巡检而设计。通过地面车携带大容量电池,经由缆绳为无人机持续供电,显著延长其作业时间。系统基于市售组件构建硬件架构,确保可复现性,并采用基于机器人操作系统(ROS)的全栈软件框架,包含开源组件。软件支持基于直接激光雷达定位(DLL)的精确定位,以及集成式地面车-缆绳-无人机系统的安全路径规划与协同轨迹跟踪。通过三类实地实验验证:(i)三次手动飞行续航测试以评估运行时长;(ii)三次定位与轨迹跟踪验证;(iii)三次自主巡检任务演示。实验结果表明系统在无卫星信号环境下具备鲁棒性与自主性。所有实验数据已公开,供复现与基准测试使用。

原文摘要 · Abstract (English)

Unmanned Aerial Vehicles (UAVs) have become essential tools in inspection and emergency response operations due to their high maneuverability and ability to access hard-to-reach areas. However, their limited battery life significantly restricts their use in long-duration missions. This paper presents a tethered marsupial robotic system composed of a UAV and an Unmanned Ground Vehicle (UGV), specifically designed for autonomous, long-duration inspection tasks in Global Navigation Satellite System (GNSS)-denied environments. The system extends the UAV's operational time by supplying power through a tether connected to high-capacity battery packs carried by the UGV. Our work details the hardware architecture based on off-the-shelf components to ensure replicability and describes our full-stack software framework used by the system, which is composed of open-source components and built upon the Robot Operating System (ROS). The proposed software architecture enables precise localization using a Direct LiDAR Localization (DLL) method and ensures safe path planning and coordinated trajectory tracking for the integrated UGV-tether-UAV system. We validate the system through three sets of field experiments involving (i) three manual flight endurance tests to estimate the operational duration, (ii) three experiments for validating the localization and the trajectory tracking systems, and (iii) three executions of an inspection mission to demonstrate autonomous inspection capabilities. The results of the experiments confirm the robustness and autonomy of the system in GNSS-denied environments. Finally, all experimental data have been made publicly available to support reproducibility and to serve as a common open dataset for benchmarking.

无人机巡检系绳系统自主导航机器人协同

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