A kind of route planning method for UAV based on improved PSO algorithm

Qingbo Geng, Zheng Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

27 Citations (Scopus)

Abstract

This paper studies the basic model of the UAV track planning. As basic Particle Swarm Optimization (PSO) algorithm is easy to fall into local minimum and its searching accuracy is not ideal, the author puts forward an improved hybrid particle swarm UAV route planning method with contraction factor. This method is used to change algorithm in the balance of performance by introducing contraction factor and learning factor, in order to get a better convergence speed and convergence rate. At the same time using MATLAB as the development tool for simulation, the results show that this method is simple and effective, and can meet the requirements of the UAV path planning.

Original languageEnglish
Title of host publication2013 25th Chinese Control and Decision Conference, CCDC 2013
Pages2328-2331
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 25th Chinese Control and Decision Conference, CCDC 2013 - Guiyang, China
Duration: 25 May 201327 May 2013

Publication series

Name2013 25th Chinese Control and Decision Conference, CCDC 2013

Conference

Conference2013 25th Chinese Control and Decision Conference, CCDC 2013
Country/TerritoryChina
CityGuiyang
Period25/05/1327/05/13

Keywords

  • Improved hybrid particle swarm
  • UAV
  • path planning

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