Three-Dimensional Path Planning of UAV Based on Improved Particle Swarm Optimization

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Název: Three-Dimensional Path Planning of UAV Based on Improved Particle Swarm Optimization
Autoři: Lixia Deng, Huanyu Chen, Xiaoyiqun Zhang, Haiying Liu
Zdroj: Mathematics ; Volume 11 ; Issue 9 ; Pages: 1987
Informace o vydavateli: Multidisciplinary Digital Publishing Institute
Rok vydání: 2023
Sbírka: MDPI Open Access Publishing
Témata: particle swarm algorithm, UAV, 3D path planning, SHADE algorithm
Popis: The traditional particle swarm optimization algorithm is fast and efficient, but it is easy to fall into a local optimum. An improved PSO algorithm is proposed and applied in 3D path planning of UAV to solve the problem. Improvement methods are described as follows: combining PSO algorithm with genetic algorithm (GA), setting dynamic inertia weight, adding sigmoid function to improve the crossover and mutation probability of genetic algorithm, and changing the selection method. The simulation results show that the improved PSO algorithm solves better route results and is faster and more stable.
Druh dokumentu: text
Popis souboru: application/pdf
Jazyk: English
Relation: C2: Dynamical Systems; https://dx.doi.org/10.3390/math11091987
DOI: 10.3390/math11091987
Dostupnost: https://doi.org/10.3390/math11091987
Rights: https://creativecommons.org/licenses/by/4.0/
Přístupové číslo: edsbas.EE1BE8C2
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  Label: Title
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  Data: Three-Dimensional Path Planning of UAV Based on Improved Particle Swarm Optimization
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  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Lixia+Deng%22">Lixia Deng</searchLink><br /><searchLink fieldCode="AR" term="%22Huanyu+Chen%22">Huanyu Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Xiaoyiqun+Zhang%22">Xiaoyiqun Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Haiying+Liu%22">Haiying Liu</searchLink>
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  Data: Mathematics ; Volume 11 ; Issue 9 ; Pages: 1987
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  Data: Multidisciplinary Digital Publishing Institute
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  Data: 2023
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  Data: <searchLink fieldCode="DE" term="%22particle+swarm+algorithm%22">particle swarm algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22UAV%22">UAV</searchLink><br /><searchLink fieldCode="DE" term="%223D+path+planning%22">3D path planning</searchLink><br /><searchLink fieldCode="DE" term="%22SHADE+algorithm%22">SHADE algorithm</searchLink>
– Name: Abstract
  Label: Description
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  Data: The traditional particle swarm optimization algorithm is fast and efficient, but it is easy to fall into a local optimum. An improved PSO algorithm is proposed and applied in 3D path planning of UAV to solve the problem. Improvement methods are described as follows: combining PSO algorithm with genetic algorithm (GA), setting dynamic inertia weight, adding sigmoid function to improve the crossover and mutation probability of genetic algorithm, and changing the selection method. The simulation results show that the improved PSO algorithm solves better route results and is faster and more stable.
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        Type: general
      – SubjectFull: UAV
        Type: general
      – SubjectFull: 3D path planning
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