Decision Modeling of UAV On-Line Path Planning Based on IMM

In order to enhance the capability of tracking targets autonomously of UAV, a model for UAV on-line path planning is established based on the theoretical framework of partially observable markov decision process(POMDP). The elements of the POMDP model are analyzed and described. According to the div...

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Format: Article
Language:zho
Published: EDP Sciences 2018-04-01
Series:Xibei Gongye Daxue Xuebao
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Online Access:https://www.jnwpu.org/articles/jnwpu/pdf/2018/02/jnwpu2018362p323.pdf
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collection DOAJ
description In order to enhance the capability of tracking targets autonomously of UAV, a model for UAV on-line path planning is established based on the theoretical framework of partially observable markov decision process(POMDP). The elements of the POMDP model are analyzed and described. According to the diversity of the target motion in real world, the law of state transition in POMDP model is described by the method of Interactive Multiple Model(IMM) To adapt to the target maneuvering changes. The action strategy of the UAV is calculated through nominal belief-state optimization(NBO) algorithm which is designed to search optimal action policy to minimize the cumulative cost of action. The generated action strategy controls the UAV flight. The simulation results show that the established POMDP model can achieve autonomous planning for UAV route, and it can control the UAV to effectively track target. The planning path is more reasonable and efficient than the result of using single state transition law.
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spelling doaj.art-828777824b9e4c0f98cb82a611da06ba2023-11-02T03:09:29ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252018-04-0136232333110.1051/jnwpu/20183620323jnwpu2018362p323Decision Modeling of UAV On-Line Path Planning Based on IMM0123School Electronics and Information, Northwestern Polytechnical UniversitySchool Electronics and Information, Northwestern Polytechnical UniversityAir Force Military Representatire Office in Jiangxi AreaSchool Electronics and Information, Northwestern Polytechnical UniversityIn order to enhance the capability of tracking targets autonomously of UAV, a model for UAV on-line path planning is established based on the theoretical framework of partially observable markov decision process(POMDP). The elements of the POMDP model are analyzed and described. According to the diversity of the target motion in real world, the law of state transition in POMDP model is described by the method of Interactive Multiple Model(IMM) To adapt to the target maneuvering changes. The action strategy of the UAV is calculated through nominal belief-state optimization(NBO) algorithm which is designed to search optimal action policy to minimize the cumulative cost of action. The generated action strategy controls the UAV flight. The simulation results show that the established POMDP model can achieve autonomous planning for UAV route, and it can control the UAV to effectively track target. The planning path is more reasonable and efficient than the result of using single state transition law.https://www.jnwpu.org/articles/jnwpu/pdf/2018/02/jnwpu2018362p323.pdfpartially observable markov decision processinteractive multiple modeluavtarget trackingmatlabcost reduction
spellingShingle Decision Modeling of UAV On-Line Path Planning Based on IMM
Xibei Gongye Daxue Xuebao
partially observable markov decision process
interactive multiple model
uav
target tracking
matlab
cost reduction
title Decision Modeling of UAV On-Line Path Planning Based on IMM
title_full Decision Modeling of UAV On-Line Path Planning Based on IMM
title_fullStr Decision Modeling of UAV On-Line Path Planning Based on IMM
title_full_unstemmed Decision Modeling of UAV On-Line Path Planning Based on IMM
title_short Decision Modeling of UAV On-Line Path Planning Based on IMM
title_sort decision modeling of uav on line path planning based on imm
topic partially observable markov decision process
interactive multiple model
uav
target tracking
matlab
cost reduction
url https://www.jnwpu.org/articles/jnwpu/pdf/2018/02/jnwpu2018362p323.pdf