Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Zhining, Zhang, Long, Ma, Xiaoshan, Liu, Yang, Yang, Lin, Yang, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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
_version_ 1784675175486193664
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
work_keys_str_mv AT xuzhining anantidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT zhanglong anantidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT maxiaoshan anantidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT liuyang anantidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT yanglin anantidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT yangfeng anantidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT xuzhining antidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT zhanglong antidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT maxiaoshan antidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT liuyang antidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT yanglin antidisturbanceresilienceenhancedalgorithmforuav3drouteplanning
AT yangfeng antidisturbanceresilienceenhancedalgorithmforuav3drouteplanning