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Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks
This paper considers a laser-powered unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system. In the system, a UAV is dispatched as an energy transmitter to replenish energy for battery-limited sensors in a wireless rechargeable sensor network (WRSN) by transferring radio frequenc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738894/ https://www.ncbi.nlm.nih.gov/pubmed/36501917 http://dx.doi.org/10.3390/s22239215 |
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author | Liu, Ning Luo, Chuanwen Cao, Jia Hong, Yi Chen, Zhibo |
author_facet | Liu, Ning Luo, Chuanwen Cao, Jia Hong, Yi Chen, Zhibo |
author_sort | Liu, Ning |
collection | PubMed |
description | This paper considers a laser-powered unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system. In the system, a UAV is dispatched as an energy transmitter to replenish energy for battery-limited sensors in a wireless rechargeable sensor network (WRSN) by transferring radio frequency (RF) signals, and a mobile unmanned vehicle (MUV)-loaded laser transmitter travels on a fixed path to charge the on-board energy-limited UAV when it arrives just below the UAV. Based on the system, we investigate the trajectory optimization of laser-charged UAVs for charging WRSNs (TOLC problem), which aims to optimize the flight trajectories of a UAV and the travel plans of an MUV cooperatively to minimize the total working time of the UAV so that the energy of every sensor is greater than or equal to the threshold. Then, we prove that the problem is NP-hard. To solve the TOLC problem, we first propose the weighted centered minimum coverage (WCMC) algorithm to cluster the sensors and compute the weighted center of each cluster. Based on the WCMC algorithm, we propose the TOLC algorithm (TOLCA) to design the detailed flight trajectory of a UAV and the travel plans of an MUV, which consists of the flight trajectory of a UAV, the hovering points of a UAV with the corresponding hovering times used for the charging sensors, the hovering points of a UAV with the corresponding hovering times used for replenishing energy itself, and the hovering times of a UAV waiting for an MUV. Numerical results are provided to verify that the suggested strategy provides an effective method for supplying wireless rechargeable sensor networks with sustainable energy. |
format | Online Article Text |
id | pubmed-9738894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97388942022-12-11 Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks Liu, Ning Luo, Chuanwen Cao, Jia Hong, Yi Chen, Zhibo Sensors (Basel) Article This paper considers a laser-powered unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system. In the system, a UAV is dispatched as an energy transmitter to replenish energy for battery-limited sensors in a wireless rechargeable sensor network (WRSN) by transferring radio frequency (RF) signals, and a mobile unmanned vehicle (MUV)-loaded laser transmitter travels on a fixed path to charge the on-board energy-limited UAV when it arrives just below the UAV. Based on the system, we investigate the trajectory optimization of laser-charged UAVs for charging WRSNs (TOLC problem), which aims to optimize the flight trajectories of a UAV and the travel plans of an MUV cooperatively to minimize the total working time of the UAV so that the energy of every sensor is greater than or equal to the threshold. Then, we prove that the problem is NP-hard. To solve the TOLC problem, we first propose the weighted centered minimum coverage (WCMC) algorithm to cluster the sensors and compute the weighted center of each cluster. Based on the WCMC algorithm, we propose the TOLC algorithm (TOLCA) to design the detailed flight trajectory of a UAV and the travel plans of an MUV, which consists of the flight trajectory of a UAV, the hovering points of a UAV with the corresponding hovering times used for the charging sensors, the hovering points of a UAV with the corresponding hovering times used for replenishing energy itself, and the hovering times of a UAV waiting for an MUV. Numerical results are provided to verify that the suggested strategy provides an effective method for supplying wireless rechargeable sensor networks with sustainable energy. MDPI 2022-11-27 /pmc/articles/PMC9738894/ /pubmed/36501917 http://dx.doi.org/10.3390/s22239215 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Ning Luo, Chuanwen Cao, Jia Hong, Yi Chen, Zhibo Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks |
title | Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks |
title_full | Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks |
title_fullStr | Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks |
title_full_unstemmed | Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks |
title_short | Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks |
title_sort | trajectory optimization of laser-charged uavs for charging wireless rechargeable sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738894/ https://www.ncbi.nlm.nih.gov/pubmed/36501917 http://dx.doi.org/10.3390/s22239215 |
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