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Disaster Reconnaissance Using Multiple Small Unmanned Aerial Vehicles
Author(s) -
Jeffrey C. Derricott,
Jacob B. Willis,
Cameron K. Peterson,
Kevin W. Franke,
John D. Hedengren
Publication year - 2019
Publication title -
mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.117
H-Index - 17
eISSN - 1943-5649
pISSN - 0025-6501
DOI - 10.1115/1.2019-jun5
Subject(s) - geospatial analysis , merge (version control) , computer science , fidelity , high fidelity , task (project management) , systems engineering , artificial intelligence , aeronautics , engineering , remote sensing , telecommunications , electrical engineering , information retrieval , geology
Small rotorcraft unmanned air vehicles (sUAVs) are valuable tools in solving geospatial inspection challenges. One area where this is being widely explored is disaster reconnaissance [1]. Using sUAVs to collect images provides engineers and government officials critical information about the conditions before and after a disaster [2]. This is accomplished by creating high- fidelity 3D models from the sUAV’s imagery. However, using an sUAV to perform inspections is a challenging task due to constraints on the vehicle’s flight time, computational power, and data storage capabilities [3]. The approach presented in this article illustrates a method for utilizing multiple sUAVs to inspect a disaster region and merge the separate data into a single high-resolution 3D model.

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