Aerial mapping systems are important for many surveying applications (e.g., industrial inspection or agricultural monitoring). Aerial platforms that can fly GPS-guided preplanned missions semi-autonomously are 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 LiDAR-based 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. 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 $2528$ 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：空中测绘系统对工业巡检、农业监测等调查应用至关重要。目前，能够半自主执行GPS引导预编程任务的飞行平台已广泛可用，但全自主系统可显著提升效率。自主测绘复杂三维结构需要在线建图与任务规划协同运行的系统。本文提出Osprey——一种具备先进多会话LiDAR建图能力的自主空中测绘系统，使非专业操作员可通过指定有界目标区域，令飞行平台在多次飞行中自主完成测绘。野外实验表明，与人工操控飞行平台或地面激光扫描仪（TLS）的测量方式相比，该系统能够对大型工业场地实现更优的测绘覆盖范围。在总计2528平方米、最大高度27米的三个场地中，通过112分钟自主飞行时间完成分任务测绘。采用点云与NeRF重建方法，由Osprey捕获的图像生成真彩色地图，为结构检测任务提供了有效数据支撑。