Osprey: LiDAR SLAMと次善視点計画による複数セッション自律空中マッピング
Osprey: Multi-Session Autonomous Aerial Mapping with LiDAR-based SLAM and Next Best View Planning
LiDARベースのSLAMと次善視点計画を組み合わせ、非専門家が指定した領域を複数回の飛行で自律的にマッピングする空中システムを開発し、産業現場での実証実験で手動調査を上回るカバレッジを達成した。
著者: Rowan Border, Nived Chebrolu, Yifu Tao, Jonathan D. Gammell, Maurice Fallon
分類: cs.RO
原文アブストラクト
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.
