无人机引导无人机：在杂乱环境中协同导航装备较少的微型飞行器
Drones Guiding Drones: Cooperative Navigation of a Less-Equipped Micro Aerial Vehicle in Cluttered Environments
AI总结：
本文提出一种协同导航框架，由主无人机携带重传感器构建地图并规划路径，引导装备较少的次级无人机在杂乱GNSS拒止环境中自主导航，通过真实实验验证了其有效性。
摘要：
在杂乱未知环境中可靠部署无人驾驶飞行器（UAV）需要精确的传感器，以实现在全球导航卫星系统（GNSS）拒止环境中的定位和避障。这一要求限制了具有有限载荷能力的廉价和微型飞行器的使用，如果要求工业级可靠性和精度的话。本文研究了将携带重型传感器的必要性卸载给无人机团队中另一成员的可能性，同时保持旨在探索狭窄通道的较小机器人的期望能力。提出了一种新颖的协同引导框架，将传感需求从最小化的次级无人机卸载到更高级的主无人机。主无人机构建环境的密集占据地图，并为两架无人机规划无碰撞路径，以确保即使在较大机器人无法进入的区域也能到达次级无人机的目标。主无人机引导次级无人机遵循规划路径，同时使用基于激光雷达（LiDAR）的相对定位来跟踪无人机。所提出的方法在真实世界实验中得到了验证，实验中使用了一个异构团队，包括一架配备3D LiDAR的主无人机和一架配备摄像头的微型次级无人机，它们在未知的杂乱GNSS拒止环境中自主移动，所提出的框架完全在无人机上运行。
英文摘要：
Reliable deployment of Unmanned Aerial Vehicles (UAVs) in cluttered unknown environments requires accurate sensors for Global Navigation Satellite System (GNSS)-denied localization and obstacle avoidance. Such a requirement limits the usage of cheap and micro-scale vehicles with constrained payload capacity if industrial-grade reliability and precision are required. This paper investigates the possibility of offloading the necessity to carry heavy sensors to another member of the UAV team while preserving the desired capability of the smaller robot intended for exploring narrow passages. A novel cooperative guidance framework offloading the sensing requirements from a minimalistic secondary UAV to a superior primary UAV is proposed. The primary UAV constructs a dense occupancy map of the environment and plans collision-free paths for both UAVs to ensure reaching the desired secondary UAV's goals even in areas not accessible by the bigger robot. The primary UAV guides the secondary UAV to follow the planned path while tracking the UAV using Light Detection and Ranging (LiDAR)-based relative localization. The proposed approach was verified in real-world experiments with a heterogeneous team of a 3D LiDAR-equipped primary UAV and a micro-scale camera-equipped secondary UAV moving autonomously through unknown cluttered GNSS-denied environments with the proposed framework running fully on board the UAVs.
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。
