基于改进遗传算法的多无人机航路规划方法  

Method of Path Planning for Multi-UAV Based on Improved Genetic Algorithm

作　　者：刘超[1] LIU Chao(Key Laboratory of Flight Simulation,Chinese Flight Test Establishment,Xi’an 710089,China)

机构地区：[1]中国飞行试验研究院飞行仿真航空科技重点实验室,西安710089

出　　处：《火力与指挥控制》2019年第1期18-22,共5页Fire Control & Command Control

基　　金：航空科学基金资助项目(20151396013)

摘　　要：在分析多无人侦察机任务需求、限制以及特性等要素基础上,建立了多无人机航路规划优化模型。以航程作为性能指标,将多无人机侦察多目标航路规划转化为多旅行商问题。通过对多旅行商问题特点分析,采用遗传算法基本思想,对编码和适应度函数以及操作算子进行合理设计,并改进了交叉和变异操作算子以取得更好优化结果。仿真结果表明所提算法的合理性和有效性。A multi -UAVs (Unmanned Aerial Vehicles)path planning model optimization is established by analyzing the task requirement,restrictions and character. In consideration of journey as the system consumption to evaluate performance,reconnaissance path planning of multi-UAV can be regarded as MTSP(Multiple Traveling Salesmen Problem). Reasonable coding,improved crossover and variation genetic operators were selected combing the feature of MTSP and the basic idea of Genetic Algorithm. The result of simulation demonstrates that the aforementioned method is reasonable and effective.

关 键 词：多无人机侦察 航路规划 MTSP问题 改进遗传算法 

分 类 号：V218[航空宇航科学与技术—航空宇航推进理论与工程] TJ810[兵器科学与技术—武器系统与运用工程]