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An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning
Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carri...
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/PMC8950578/ https://www.ncbi.nlm.nih.gov/pubmed/35336320 http://dx.doi.org/10.3390/s22062151 |
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author | Xu, Zhining Zhang, Long Ma, Xiaoshan Liu, Yang Yang, Lin Yang, Feng |
author_facet | Xu, Zhining Zhang, Long Ma, Xiaoshan Liu, Yang Yang, Lin Yang, Feng |
author_sort | Xu, Zhining |
collection | PubMed |
description | Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carried out in a targeted manner. First of all, in order to ensure the safety of the UAV design, we focus on the capabilities of the UAV body and build a risk identification, assessment, and modeling method such that the mission control parameters of the UAV can be determined. Then, the three-dimensional route planning algorithm based on the artificial potential fields algorithm is used to ensure the safe operation of the UAV online and in real time. At the same time, by adjusting the discriminant coefficient of potential risks in real time to deal with time-varying random disturbance encountered by the UAV, the resilience of the UAV 3D flight route planning can be improved. Finally, the effectiveness of the algorithm is verified by the simulation. The simulation results show that the REPARE algorithm can effectively solve the traditional route planning algorithm’s insufficiency in anti-disturbance. It is safer than a traditional A* route planning algorithm, and its running time is shorter than that of the traditional artificial potential field route planning algorithm. It solves the problems of local optimization, enhances the UAV’s ability to tolerate general uncertain disturbances, and eventually improves resilience of the system. |
format | Online Article Text |
id | pubmed-8950578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89505782022-03-26 An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning Xu, Zhining Zhang, Long Ma, Xiaoshan Liu, Yang Yang, Lin Yang, Feng Sensors (Basel) Article Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carried out in a targeted manner. First of all, in order to ensure the safety of the UAV design, we focus on the capabilities of the UAV body and build a risk identification, assessment, and modeling method such that the mission control parameters of the UAV can be determined. Then, the three-dimensional route planning algorithm based on the artificial potential fields algorithm is used to ensure the safe operation of the UAV online and in real time. At the same time, by adjusting the discriminant coefficient of potential risks in real time to deal with time-varying random disturbance encountered by the UAV, the resilience of the UAV 3D flight route planning can be improved. Finally, the effectiveness of the algorithm is verified by the simulation. The simulation results show that the REPARE algorithm can effectively solve the traditional route planning algorithm’s insufficiency in anti-disturbance. It is safer than a traditional A* route planning algorithm, and its running time is shorter than that of the traditional artificial potential field route planning algorithm. It solves the problems of local optimization, enhances the UAV’s ability to tolerate general uncertain disturbances, and eventually improves resilience of the system. MDPI 2022-03-10 /pmc/articles/PMC8950578/ /pubmed/35336320 http://dx.doi.org/10.3390/s22062151 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 Xu, Zhining Zhang, Long Ma, Xiaoshan Liu, Yang Yang, Lin Yang, Feng An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning |
title | An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning |
title_full | An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning |
title_fullStr | An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning |
title_full_unstemmed | An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning |
title_short | An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning |
title_sort | anti-disturbance resilience enhanced algorithm for uav 3d route planning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950578/ https://www.ncbi.nlm.nih.gov/pubmed/35336320 http://dx.doi.org/10.3390/s22062151 |
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