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Journal article

Osprey: multisession autonomous aerial mapping with LiDAR-based SLAM and next best view planning

Abstract:

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 semiautonomously are already widely available, but fully autonomous systems can significantly improve efficiency. Autonomously mapping complex 3-D structures requires a system that performs online mapping and mission planning. This article presents Osprey, an autonomous aerial mapping system with state-of-the-art multisession light detection and ranging (LiDAR)-based mapping capabilities. It enables a nonexpert 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 m2 and a maximum height of 27 m, were mapped in separate missions using 112 min of autonomous flight time. True-color maps were created from images captured by Osprey using pointcloud and neural radiance field (NeRF) reconstruction methods. These maps provide useful data for structural inspection tasks.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/tfr.2024.3432031

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0003-2940-0879


More from this funder
Funder identifier:
https://ror.org/03wnrjx87
Grant:
UF160148
More from this funder
Funder identifier:
https://ror.org/001aqnf71
Grant:
10037847


Publisher:
IEEE
Journal:
IEEE Transactions on Field Robotics More from this journal
Volume:
1
Pages:
113-130
Publication date:
2024-07-24
Acceptance date:
2024-07-04
DOI:
EISSN:
2997-1101


Language:
English
Keywords:
Pubs id:
2018918
Local pid:
pubs:2018918
Deposit date:
2024-10-15
ARK identifier:

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