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

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Titel: Three-Dimensional Path Planning of UAV Based on Improved Particle Swarm Optimization
Autoren: Lixia Deng, Huanyu Chen, Xiaoyiqun Zhang, Haiying Liu
Quelle: Mathematics ; Volume 11 ; Issue 9 ; Pages: 1987
Verlagsinformationen: Multidisciplinary Digital Publishing Institute
Publikationsjahr: 2023
Bestand: MDPI Open Access Publishing
Schlagwörter: particle swarm algorithm, UAV, 3D path planning, SHADE algorithm
Beschreibung: 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.
Publikationsart: text
Dateibeschreibung: application/pdf
Sprache: English
Relation: C2: Dynamical Systems; https://dx.doi.org/10.3390/math11091987
DOI: 10.3390/math11091987
Verfügbarkeit: https://doi.org/10.3390/math11091987
Rights: https://creativecommons.org/licenses/by/4.0/
Dokumentencode: edsbas.EE1BE8C2
Datenbank: BASE
Beschreibung
Abstract: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.
DOI:10.3390/math11091987