基于改进遗传算法的协同航迹规划方法  

A Cooperative Trajectory Planning Method Based on Improved Genetic Algorithm

作　　者：唐颂 吴建源 TANG Song;WU Jianyuan(South China University of Technology,Guangzhou 510000,China;No.75833 Unit of PLA,Guangzhou 510000,China)

机构地区：[1]华南理工大学,广州510000 [2]中国人民解放军75833部队,广州510000

出　　处：《电光与控制》2024年第7期8-12,26,共6页Electronics Optics & Control

基　　金：国家社会科学基金(2020-SKJJ-C-004);湖南科技大学开放基金(E22229)。

摘　　要：针对多无人机协同规划问题求解规模大、效率低的问题,提出了一种单-双亲遗传算法(PBGA)求解模型。该算法具有改进的编码方法和一种单双亲结合的进化策略,由单亲遗传算子进行种群进化,由双亲遗传算子跳出局部最优。仿真结果显示,PBGA具有收敛性,在小规模和大规模寻优算例中分别比传统遗传算法减少了70%和64%的收敛代数,对解决多无人机协同问题具有一定的参考价值。To address the issues of large computation scale and low efficiency of multi-UAV cooperative planning a Partheno-/Bi-Parent Genetic Algorithm(PBGA)solving model is proposed.This algorithm features an improved encoding method and a single-double parent combined evolutionary strategy.The population evolution is carried out by a partheno-genetic operator while the bi-parent genetic operator helps to escape from local optima.Simulation results demonstrate the convergence of PBGA.In small-scale and large-scale optimization scenarios PBGA reduces the convergence iterations by 70%and 64%respectively compared with the traditional genetic algorithm.This approach holds significant reference value for addressing multi-UAV cooperative problems.

关 键 词：多无人机 任务分配 航迹规划 改进编码 单双亲遗传算法 

分 类 号：V249[航空宇航科学与技术—飞行器设计] TP273[自动化与计算机技术—检测技术与自动化装置]