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Estimation, Search, and Planning (ESP) Research Group

Osprey: Multi-session autonomous aerial mapping with lidar-based slam and next best view planning

Authors
  1. Rowan Border
  2. Nived Chebrolu
  3. Yifu Tao
  4. Jonathan D. Gammell
  5. Maurice Fallon
Publication Date
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 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 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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Publication Details
Type
Journal Paper
Journal
Field Robotics
arXiv Identifier
2311.03484 [cs.RO]
Notes
To Appear, Manuscript #FR-23-0016
Manuscript
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BibTeX Entry
@article{border_tfr24,
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 = {2024},
}