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