Osprey: Multi-session autonomous aerial mapping with lidar-based slam and next best view planning
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- Abstract
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 m2 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.
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- Journal Paper
- Journal
- Field Robotics
- arXiv Identifier
- 2311.03484 [cs.RO]
- Notes
- Submitted, Manuscript #FR-23-0016
- Manuscript
- Open-Access PDF
- https://arxiv.org/pdf/2311.03484
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- BibTeX Entry
@article{border_arxiv23,
author = {Rowan Border and Nived Chebrolu and Yifu Tao and Jonathan D Gammell and Maurice Fallon},
title = {{\emph{Osprey}}: Multi-session autonomous aerial mapping with lidar-based slam and next best view planning},
journal = {Field Robotics},
year = {2023},
note = {Submitted, Manuscript \#FR-23-0016, {arXiv}:2311.03484 {[cs.RO]}},
}