火力与指挥控制2024，Vol.49Issue(4)：18-23,6.DOI:10.3969/j.issn.1002-0640.2024.04.003
基于分组教与学的无人战斗机自适应路径规划
Adaptive Path Planning of UCAV with Modified Teaching-learning-based Optimization
摘要
Abstract
Aiming at the path planning problem of Unmanned Combat Air Vehicle(UCAV)in the battlefield where UCAV is located in a threat area,a UCAV adaptive path planning method based on the algorithm of modified teaching-learning-based optimization is proposed.By analyzing the evaluation index of UCAV path,an adaptive UCAV path evaluation model is proposed,and the mission path with short distance and small threat is planned according to the combat environment.Then,aiming at the problems of low precision and long time consuming in the optimization of teaching and learning algorithm,the algorithm of modified teaching-learning-based optimization is proposed,and dynamic grouping and Gaussian distribution perturbation strategy are introduced to improve the optimization performance of the algorithm.The simulation results show that the optimal path is shorter and safer.关键词
无人战斗机/路径规划/教与学算法/群体智能Key words
unmanned combat air vehicle(UCAV)/path planning/modified teaching-learning-based optimization/swarm intelligence分类
信息技术与安全科学引用本文复制引用
唐天兵,陈永发,蒙祖强,李继发..基于分组教与学的无人战斗机自适应路径规划[J].火力与指挥控制,2024,49(4):18-23,6.基金项目
国家自然科学基金资助项目(62266004) （62266004）
