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

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 gene...

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Bibliographic Details
Main Authors: Chen, H. (Author), Deng, L. (Author), Liu, H. (Author), Zhang, X. (Author)
Format: Article
Language:English
Published: MDPI 2023
Subjects:
UAV
Online Access:View Fulltext in Publisher
View in Scopus
LEADER 01454nam a2200229Ia 4500
001 10.3390-math11091987
008 230529s2023 CNT 000 0 und d
020 |a 22277390 (ISSN) 
245 1 0 |a Three-Dimensional Path Planning of UAV Based on Improved Particle Swarm Optimization 
260 0 |b MDPI  |c 2023 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/math11091987 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159228923&doi=10.3390%2fmath11091987&partnerID=40&md5=81d32ba76711cc2d177ac2655762d9d7 
520 3 |a 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. © 2023 by the authors. 
650 0 4 |a 3D path planning 
650 0 4 |a particle swarm algorithm 
650 0 4 |a SHADE algorithm 
650 0 4 |a UAV 
700 1 0 |a Chen, H.  |e author 
700 1 0 |a Deng, L.  |e author 
700 1 0 |a Liu, H.  |e author 
700 1 0 |a Zhang, X.  |e author 
773 |t Mathematics