基于改进遗传算法的异构多无人机任务分配  

Cooperative Task Assignment for Heterogeneous Multi-UAVs Based on Improved Genetic Algorithm

作　　者：王婷[1] 符小卫[1] 高晓光[1] 

机构地区：[1]西北工业大学电子信息学院,西安710129

出　　处：《火力与指挥控制》2013年第5期37-41,共5页Fire Control & Command Control

基　　金：2011高校博士点基金(20116102110026);西工大基础研究基金资助项目(JC201012)

摘　　要：针对异构多无人机协同任务分配问题,提出了一种基于改进的遗传算法的多UAV任务分配方法。根据多UAV协同任务分配问题的特点,设计了新的遗传算子,并且对适应度值做了标定,有效避免了算法在最优解附近摆动现象的发生,从而提高了任务分配的效率。充分利用改进遗传算法的全局搜索能力,有效地解决多约束条件下多UAV协同目标分配问题。仿真结果表明,改进的遗传算法能够稳定快速地找到较优分配方案,并且算法简单有效。Aiming at the problem of multi heterogeneous UAVs cooperative task assignment,a task assignment method for heterogeneous multi-UAVs had been presented, which based on improved genetic algorithm. According to the characteristics of muhi-UAV cooperative task assignment, a new genetic operators is designed and the value of the fitness is calibrated to avoid effectively the phenomenon of algorithm swing？near the optimal solution, and increase？the efficiency of？task assignment. Take full advantage of the global search ability of genetic algorithms to solve multi-UAV target allocation problem under the multi-constraint coordination effectively. The simulation results show that the improved genetic algorithm can find better distribution program stability and quickly, and the algorithm is simple and effective.

关 键 词：异构无人机协同 任务分配 遗传算法 适应度值标定 

分 类 号：V279[航空宇航科学与技术—飞行器设计]