测控技术2026，Vol.45Issue(4)：20-29,10.DOI:10.19708/j.ckjs.2026.03.209
基于改进鹅优化算法的无人机路径规划方法研究
UAV Path Planning Method Based on Improved GOOSE Optimization Algorithm
摘要
Abstract
To address the problems that swarm-intelligence optimization algorithms encounter in UAV path planning namely excessive path length,insufficient path smoothness,and inadequate convergence stability,a UAV path planning method based on an improved goose optimization algorithm(GOOSE),termed GOOSE_DE,is proposed.In this method,a Sobol sequence and an opposition-based learning strategy are combined to opti-mize the initial population.A bidirectional information interaction mechanism and an intelligent selection strat-egy based on solution quality are adopted to balance global exploration and local exploitation.Furthermore,stage-wise strategy adjustment,the complementary enhancement of population diversity,and the dynamic ad-justment of the differential weight and crossover probability strengthen the algorithm's search capability and prevent it from falling into local optima.Comparative experiments are conducted against the sparrow search al-gorithm(SSA),the K-means grey wolf optimization(KMGWO)algorithm,the heterogeneous improved dynamic multi-swarm particle swarm optimization(HIDMSPSO)algorithm,the advanced-differential-evolution(ADE)al-gorithm,and the GOOSE.The results show that GOOSE_DE exhibits good convergence accuracy and stability on standard benchmark test functions.In path planning experiments on 20×20 and 30×30 grid maps,GOOSE_DE achieves the shortest average path length compared with the other five algorithms,with strong robustness and better smoothness,which fully verifies the proposed method's performance in path optimization,smoothness improvement,and robustness enhancement.关键词
路径规划/鹅优化算法/差分进化算法/分阶段自适应策略/参数优化Key words
path planning/goose optimization algorithm(GOOSE)/differential evolution algorithm/phased a-daptive strategy/parameter optimization分类
航空航天引用本文复制引用
张育玮,韩朝怡,赵茹,程永喜..基于改进鹅优化算法的无人机路径规划方法研究[J].测控技术,2026,45(4):20-29,10.基金项目
国家自然科学基金(11804245) （11804245）
