Research on multi-constraint fusion PLO path planning algorithm for UAV in 3D environment
YANG Hui
YANG Duanzheng
DONG Yuchong
XIE Xiuna
LIANG Cheng
CHEN Peng
Abstract：To address the insufficient search capability of the Polar Lights Optimizer(PLO)algorithm during the later stage of unmanned aerial vehicle(UAV)path planning,an improved algorithm PLO-CHV incorporating a horizontal-vertical crossover strategy is proposed.This algorithm enhances population diversity by promoting genetic recombination among individuals within the same generation through a horizontal crossover mechanism.Together with a vertical crossover mechanism,it enables cross-generational information fusion between historical optima and current individuals,thereby strengthening local search capability and achieving a balanced trade-off between global exploration and local exploitation.Simulation results demonstrate that compared to the standard PLO algorithm,the improved PLO-CHV algorithm reduces the fitness value by 89.33%in a 3D gridded environment,while decreasing the average flight altitude and path length by 6.55%and 26.79%respectively.The proposed algorithm outperforms comparison algorithms such as GA and SOGWO in convergence speed,path length and altitude.
Keywords：unmanned aerial vehiclesintelligent algorithmspath planning3D environmental modeling
Publication Date：2025-12-25
Online Publishing Date：2026-01-27(First online date of this platform, not the publication date of the document)
Pages：6( 1-6 )