Aerial mapping systems are important for many surveying applications (e.g., industrial inspection or agricultural monitoring). Semi-autonomous mapping with GPS-guided aerial platforms that fly preplanned missions is already widely available but fully autonomous systems can significantly improve efficiency. Autonomously mapping complex 3D structures requires a system that performs online mapping and mission planning. This paper presents Osprey, an autonomous aerial mapping system with state-of-the-art multi-session mapping capabilities. It enables a non-expert operator to specify a bounded target area that the aerial platform can then map autonomously, over multiple flights if necessary. Field experiments with Osprey demonstrate that this system can achieve greater map coverage of large industrial sites than manual surveys with a pilot-flown aerial platform or a terrestrial laser scanner (TLS). Three sites, with a total ground coverage of $7085$ m$^2$ and a maximum height of $27$ m, were mapped in separate missions using $112$ minutes of autonomous flight time. True colour maps were created from images captured by Osprey using pointcloud and NeRF reconstruction methods. These maps provide useful data for structural inspection tasks.

翻译：空中测绘系统对许多测量应用（如工业检测或农业监测）至关重要。利用GPS引导的空中平台执行预规划任务的半自主测绘已广泛应用，但全自主系统能显著提升效率。自主测绘复杂三维结构需要系统具备在线建图和任务规划能力。本文提出Osprey——一种具备先进多会话建图能力的自主空中测绘系统。该系统使非专业操作员能指定有界目标区域，随后空中平台可自主完成该区域的建图（必要时可跨多次飞行）。现场实验表明，Osprey在大型工业场地的测绘覆盖率上优于由飞行员操控的空中平台或地面激光扫描仪（TLS）进行的人工测绘。三个总地面覆盖面积为$7085$ m$^2$、最大高度为$27$ m的场地，通过独立任务完成测绘，自主飞行总时长为$112$分钟。利用Osprey采集的图像，通过点云和NeRF重建方法生成了真彩色地图。这些地图为结构检测任务提供了有效数据。