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DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints
We consider an Unmanned Aerial Vehicle (UAV, also known as drone) as an aerial sink to travel along a natural landscape or rural industrial linear infrastructure to collect data from deployed sensors. We study a joint schedule problem that involves flight planning for the drone and transmission sche...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164045/ https://www.ncbi.nlm.nih.gov/pubmed/30200535 http://dx.doi.org/10.3390/s18092913 |
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author | Xiong, Runqun Shan, Feng |
author_facet | Xiong, Runqun Shan, Feng |
author_sort | Xiong, Runqun |
collection | PubMed |
description | We consider an Unmanned Aerial Vehicle (UAV, also known as drone) as an aerial sink to travel along a natural landscape or rural industrial linear infrastructure to collect data from deployed sensors. We study a joint schedule problem that involves flight planning for the drone and transmission scheduling for sensors, such that the maximum amount of data can be collected with a limited individual energy budget for the UAV and the sensors, respectively. On one hand, the flight planning decides the flight speed and flight path based on sensor locations, energy budgets, and the transmission schedule. On the other hand, the transmission schedule decides for each sensor when to deliver data and what transmission power to use based on the energy budgets and flight plan. By observing three import optimality properties, we decouple the joint problem into two subproblems: drone flight planning and sensor transmission scheduling. For the first problem, we propose a dynamic programming algorithm to produce the optimal flight planning. For the second problem, with a flight plan as input, we introduce a novel technique (water-tank), which together with dynamic programming, is the key to achieve an optimal transmission schedule that maximizes data collection. Simulations show that the separately determined flight plan and transmission schedule are near-optimal for the original joint problem. |
format | Online Article Text |
id | pubmed-6164045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61640452018-10-10 DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints Xiong, Runqun Shan, Feng Sensors (Basel) Article We consider an Unmanned Aerial Vehicle (UAV, also known as drone) as an aerial sink to travel along a natural landscape or rural industrial linear infrastructure to collect data from deployed sensors. We study a joint schedule problem that involves flight planning for the drone and transmission scheduling for sensors, such that the maximum amount of data can be collected with a limited individual energy budget for the UAV and the sensors, respectively. On one hand, the flight planning decides the flight speed and flight path based on sensor locations, energy budgets, and the transmission schedule. On the other hand, the transmission schedule decides for each sensor when to deliver data and what transmission power to use based on the energy budgets and flight plan. By observing three import optimality properties, we decouple the joint problem into two subproblems: drone flight planning and sensor transmission scheduling. For the first problem, we propose a dynamic programming algorithm to produce the optimal flight planning. For the second problem, with a flight plan as input, we introduce a novel technique (water-tank), which together with dynamic programming, is the key to achieve an optimal transmission schedule that maximizes data collection. Simulations show that the separately determined flight plan and transmission schedule are near-optimal for the original joint problem. MDPI 2018-09-02 /pmc/articles/PMC6164045/ /pubmed/30200535 http://dx.doi.org/10.3390/s18092913 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xiong, Runqun Shan, Feng DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints |
title | DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints |
title_full | DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints |
title_fullStr | DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints |
title_full_unstemmed | DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints |
title_short | DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints |
title_sort | dronetank: planning uavs’ flights and sensors’ data transmission under energy constraints |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164045/ https://www.ncbi.nlm.nih.gov/pubmed/30200535 http://dx.doi.org/10.3390/s18092913 |
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