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dc.contributor.advisor | Wan, Yan | |
dc.contributor.advisor | Wan, Yan | |
dc.contributor.advisor | Dogan, Atilla | |
dc.creator | Pinheiro, Murilo Augsto | |
dc.date.accessioned | 2019-05-28T22:04:55Z | |
dc.date.available | 2019-05-28T22:04:55Z | |
dc.date.created | 2019-05 | |
dc.date.issued | 2019-04-29 | |
dc.date.submitted | May 2019 | |
dc.identifier.uri | http://hdl.handle.net/10106/28137 | |
dc.description.abstract | This work focuses on the roles of on-board sensing and off-board sensing through wireless communication for UAV missions. Employing UAV path planning under spatiotemporal wind effect as a case study, this work implements a modeling framework composed by the vehicle dynamics, environmental effect and communication model that transmits wind field data. Based on the analysis of the minimum-time optimal UAV path planning solution under communication constraints and spatiotemporal wind impact, this work obtains quantitative insights into the effect of communication quality and information update configuration on the performance of path planning. This study finds that on-board sensing and off-board sensing can both enhance the planning performance, however the performance of off-board sensing deteriorates as the communication conditions progressively get worse. Moreover, the path planning performance can be optimized if the information update parameters are correctly chosen subject to the channel capacity constraints. Ultimately, this work designs and validates an UAV navigation system which is an initial and essential step for a practical implementation of the path planning developed in this documents. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.subject | UAV communication | |
dc.subject | UAV path planning | |
dc.title | ON THE ANALYSIS OF ON-BOARD SENSING AND OFF-BOARD SENSING THROUGH WIRELESS COMMUNICATION FOR UAV PATH PLANNING IN WIND FIELDS | |
dc.type | Thesis | |
dc.degree.department | Electrical Engineering | |
dc.degree.name | Master of Science in Electrical Engineering | |
dc.date.updated | 2019-05-28T22:07:05Z | |
thesis.degree.department | Electrical Engineering | |
thesis.degree.grantor | The University of Texas at Arlington | |
thesis.degree.level | Masters | |
thesis.degree.name | Master of Science in Electrical Engineering | |
dc.type.material | text | |
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