Multi-Objective UAV Trajectory Planning in Uncertain Environment

UAV trajectory planning is one of the research focuses in artificial intelligence and UAV technology. The asymmetric information, however, will lead to the uncertainty of the UAV trajectory planning; the probability theory as the most commonly used method to solve the trajectory planning problem in...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Aoyu Zheng, Bingjie Li, Mingfa Zheng, Haitao Zhong
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	uncertainty theory asymmetry multi-objective trajectory planning particle swarm optimization Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/6b024d98a60140eca11828c43b477fc0
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6b024d98a60140eca11828c43b477fc0
record_format	dspace
spelling	oai:doaj.org-article:6b024d98a60140eca11828c43b477fc02021-11-25T19:07:14ZMulti-Objective UAV Trajectory Planning in Uncertain Environment10.3390/sym131121602073-8994https://doaj.org/article/6b024d98a60140eca11828c43b477fc02021-11-01T00:00:00Zhttps://www.mdpi.com/2073-8994/13/11/2160https://doaj.org/toc/2073-8994UAV trajectory planning is one of the research focuses in artificial intelligence and UAV technology. The asymmetric information, however, will lead to the uncertainty of the UAV trajectory planning; the probability theory as the most commonly used method to solve the trajectory planning problem in uncertain environment will lead to unrealistic conclusions under the condition of lacking samples, while the uncertainty theory based on uncertain measures is an efficient method to solve such problems. Firstly, the uncertainties in trajectory planning are sufficiently considered in this paper; the fuel consumption, concealment and threat degree with uncertain variables are taken as the objective functions; the constraints are analyzed according to the maneuverability; and the uncertain multi-objective trajectory planning (UMOTP) model is established. After that, this paper takes both the long-term benefits and its stability into account, and then, the expected-value and standard-deviation efficient trajectory model is established. What is more, this paper solves the Pareto front of the trajectory planning, satisfying various preferences, which avoids the defects of the trajectory obtained by traditional model only applicable to a certain specific situation. In order to obtain a better solution set, this paper proposes an improved backbones particle swarm optimization algorithm based on PSO and NSGA-II, which overcomes the shortcomings of the traditional algorithm such as premature convergence and poor robustness, and the efficiency of the algorithm is tested. Finally, the algorithm is applied to the UMOTP problem; then, the optimal trajectory set is obtained, and the effectiveness and reliability of the model is verified.Aoyu ZhengBingjie LiMingfa ZhengHaitao ZhongMDPI AGarticleuncertainty theoryasymmetrymulti-objectivetrajectory planningparticle swarm optimizationMathematicsQA1-939ENSymmetry, Vol 13, Iss 2160, p 2160 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	uncertainty theory asymmetry multi-objective trajectory planning particle swarm optimization Mathematics QA1-939
spellingShingle	uncertainty theory asymmetry multi-objective trajectory planning particle swarm optimization Mathematics QA1-939 Aoyu Zheng Bingjie Li Mingfa Zheng Haitao Zhong Multi-Objective UAV Trajectory Planning in Uncertain Environment
description	UAV trajectory planning is one of the research focuses in artificial intelligence and UAV technology. The asymmetric information, however, will lead to the uncertainty of the UAV trajectory planning; the probability theory as the most commonly used method to solve the trajectory planning problem in uncertain environment will lead to unrealistic conclusions under the condition of lacking samples, while the uncertainty theory based on uncertain measures is an efficient method to solve such problems. Firstly, the uncertainties in trajectory planning are sufficiently considered in this paper; the fuel consumption, concealment and threat degree with uncertain variables are taken as the objective functions; the constraints are analyzed according to the maneuverability; and the uncertain multi-objective trajectory planning (UMOTP) model is established. After that, this paper takes both the long-term benefits and its stability into account, and then, the expected-value and standard-deviation efficient trajectory model is established. What is more, this paper solves the Pareto front of the trajectory planning, satisfying various preferences, which avoids the defects of the trajectory obtained by traditional model only applicable to a certain specific situation. In order to obtain a better solution set, this paper proposes an improved backbones particle swarm optimization algorithm based on PSO and NSGA-II, which overcomes the shortcomings of the traditional algorithm such as premature convergence and poor robustness, and the efficiency of the algorithm is tested. Finally, the algorithm is applied to the UMOTP problem; then, the optimal trajectory set is obtained, and the effectiveness and reliability of the model is verified.
format	article
author	Aoyu Zheng Bingjie Li Mingfa Zheng Haitao Zhong
author_facet	Aoyu Zheng Bingjie Li Mingfa Zheng Haitao Zhong
author_sort	Aoyu Zheng
title	Multi-Objective UAV Trajectory Planning in Uncertain Environment
title_short	Multi-Objective UAV Trajectory Planning in Uncertain Environment
title_full	Multi-Objective UAV Trajectory Planning in Uncertain Environment
title_fullStr	Multi-Objective UAV Trajectory Planning in Uncertain Environment
title_full_unstemmed	Multi-Objective UAV Trajectory Planning in Uncertain Environment
title_sort	multi-objective uav trajectory planning in uncertain environment
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6b024d98a60140eca11828c43b477fc0
work_keys_str_mv	AT aoyuzheng multiobjectiveuavtrajectoryplanninginuncertainenvironment AT bingjieli multiobjectiveuavtrajectoryplanninginuncertainenvironment AT mingfazheng multiobjectiveuavtrajectoryplanninginuncertainenvironment AT haitaozhong multiobjectiveuavtrajectoryplanninginuncertainenvironment
_version_	1718410282930274304

Multi-Objective UAV Trajectory Planning in Uncertain Environment

Ejemplares similares