Osprey：基于激光雷达SLAM与下一最佳视角规划的多会话自主航空测绘
Osprey: Multi-Session Autonomous Aerial Mapping with LiDAR-based SLAM and Next Best View Planning
AI总结：
针对复杂三维结构自主测绘需求，本文提出具备多会话激光雷达测绘能力的自主航空测绘系统Osprey，可由非专业人员指定区域后多次飞行自主测绘，实地实验验证其在工业场地测绘中覆盖度优于人工与地面激光扫描方案，生成的真彩色地图可支撑结构检测。
摘要：
航空测绘系统对工业检测、农业监测等诸多测量应用至关重要。目前可在GPS引导下半自动执行预规划任务的航空平台已得到广泛应用，但全自主系统能大幅提升效率。自主测绘复杂三维结构需要一套具备在线测绘与任务规划能力的系统。本文提出Osprey——一套具备当前最优多会话激光雷达测绘能力的自主航空测绘系统。非专业操作人员只需指定一个有界目标区域，该航空平台即可通过多次飞行自主完成该区域的测绘。针对Osprey的实地实验表明，与由飞行员操控的航空平台人工测绘或地面激光扫描仪（TLS）相比，该系统对大型工业场地的地图覆盖度更高。研究在三个总地面覆盖面积达2528平方米、最高高度为27米的场地分别执行测绘任务，累计自主飞行时长为112分钟。研究利用Osprey采集的图像，通过点云与NeRF重建方法生成了真彩色地图，这些地图可为结构检测任务提供有效数据。
英文摘要：
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.
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。
