Open AccessAn Improved Particle Swarm Optimization Algorithm for Unmanned Aerial Vehicle Route Planning
Author(s) -
Xiaolu Wang,
Chen Huang,
Fuhao Chen
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2245/1/012013
Subject(s) - particle swarm optimization , waypoint , convergence (economics) , mathematical optimization , computer science , algorithm , path (computing) , motion planning , swarm behaviour , population , mathematics , real time computing , artificial intelligence , demography , sociology , robot , economics , programming language , economic growth
A global path planning method based on improved particle swarm optimization (PSO) algorithm was proposed to find a high quality flight trajectory in three-dimensional complex environment under multiple threats for UAV. The improved path planning algorithm combines the standard PSO with A* method to compensate for the slow convergence rate of PSO. The objective function with multiple constraints of A* method is used to evaluate the quality of the waypoint, and the objective function of PSO algorithm is designed to evaluate the quality of the candidate path. To verify the effectiveness of the improved algorithm, the improved PSO algorithm is used to compare with basic PSO algorithms. The experiment in complex environment shows it has stronger search ability, convergence ability due to the improvement of population diversity and convergence speed.