contributor author | Derricott, Jeffrey C. | |
contributor author | Willis, Jacob B. | |
contributor author | Peterson, Cameron K. | |
contributor author | Franke, Kevin W. | |
contributor author | Hedengren, John D. | |
date accessioned | 2019-09-18T09:02:48Z | |
date available | 2019-09-18T09:02:48Z | |
date copyright | 6/1/2019 12:00:00 AM | |
date issued | 2019 | |
identifier issn | 0025-6501 | |
identifier other | me-2019-jun5 | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4258229 | |
description abstract | 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. | |
publisher | American Society of Mechanical Engineers (ASME) | |
title | Disaster Reconnaissance Using Multiple Small Unmanned Aerial Vehicles | |
type | Journal Paper | |
journal volume | 141 | |
journal issue | 6 | |
journal title | Mechanical Engineering Magazine Select Articles | |
identifier doi | 10.1115/1.2019-JUN5 | |
journal lastpage | S11 | |
tree | Mechanical Engineering Magazine Select Articles:;2019:;volume( 141 ):;issue: 006 | |
contenttype | Fulltext | |