首页|基于改进离散粒子群的侦查无人机协同任务自动化分配方法

基于改进离散粒子群的侦查无人机协同任务自动化分配方法

Automatic Task Assignment Method for Reconnaissance UAV Based On Improved Discrete Particle Swarm Optimization

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针对现有侦查无人机协同任务分配方法存在分配时间长、分配效率较低的问题,设计一种基于改进离散粒子群的侦查无人机协同任务自动化分配方法.首先对侦查无人机协同任务指令请求进行优化,然后构建侦察无人机协同任务自动化分配组合优化模型,描述任务场景,设置约束条件和性能指标函数;最后引入随机全局与局部搜索改进离散粒子群算法,求解协同任务自动化分配组合优化模型,实现侦查无人机协同任务自动化分配.实验结果表明,提出方法对侦查无人机协同任务的分配时间均能够保持在10 s以内,任务分配目标函数最优值停留在0.98左右,执行时间迅速降低,说明该方法分配时间较短、分配速度较快,具有较高的分配效率,分配效果较好,具有一定的实用性.
Aiming at the problems of long allocation time and low efficiency in the existing cooperative task allocation methods for reconnaissance UAVs,an automatic task allocation method for reconnaissance UAVs based on improved discrete particle swarm optimization is designed.Firstly,the cooperative task command request of the reconnaissance UAV is optimized.Then the automatic assignment and combination optimization model of the reconnaissance UAV cooperative task is constructed to describe the task scenario,set constraints and performance index functions.Finally,the discrete particle swarm optimization algorithm is improved by introducing random global and local search to solve the combination optimization model of automatic assignment of cooperative tasks,so as to realize the automatic assignment of cooperative tasks of reconnaissance UAVs.The experimental results show that the allocation time of the proposed method for the cooperative tasks of the reconnaissance UAV can be kept within 10 s,the optimal value of the task allocation objective function stays at about 0.98,and the execution time decreases rapidly,indicating that the method has a shorter allocation time,faster allocation speed,higher allocation efficiency,better allocation effectiveness,and a certain degree of practicality.

improved discrete particle swarminvestigating UAVcollaborative tasksautomatic distributioncombination optimization model

蔡鑫、李卫平

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郑州警察学院 刑事科学技术系,郑州 450053

武汉理工大学 信息工程学院,武汉 430070

改进离散粒子群 侦查无人机(UAV) 协同任务 自动化分配 组合优化模型

中国高校产学研创新基金(2021)中国高校产学研创新基金-蓝点分布式智能计算项目河南省重点研发与推广专项软科学研究计划(2019)公安部公安理论软科学研究计划

2021ITA090302021LDA120151924004100682018LLYJTJXY064

2024

机械设计与研究
上海交通大学

机械设计与研究

CSTPCD北大核心
影响因子：0.531
ISSN：1006-2343
年,卷(期)：2024.40(2)
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