Task Assignment for Multi-UAV under Severe Uncertainty by Using Stochastic Multicriteria Acceptability Analysis
Task Assignment for Multi-UAV under Severe Uncertainty by Using Stochastic Multicriteria Acceptability Analysis
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DOI：
10.1155/2015/249825
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发表时间：
2015-08
影响因子：
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通讯作者：
Xiaoxuan Hu;Cheng Jing;He Luo
中科院分区：
文献类型：
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作者：
Xiaoxuan Hu;Cheng Jing;He Luo
研究了多无人机的任务分配问题。无人机将在严重不确定的环境中对一系列地面目标执行攻击任务。无人机具有不同的攻击能力，位于不同的位置。在使命开始之前，每架无人机都应该被分配一个攻击任务。由于信息的不确定性，许多任务分配所需的准则值是随机或模糊的，准则的权重也不精确。针对这一问题，提出了一种基于随机多准则可接受性分析（SMAA）的任务分配方法。分析了准则中的不确定性，设计了任务分配过程。仿真实验结果表明，该方法能有效地解决严重不确定环境下的任务分配问题。
This paper considers a task assignment problem for multiple unmanned aerial vehicles (UAVs). The UAVs are set to perform attack tasks on a collection of ground targets in a severe uncertain environment. The UAVs have different attack capabilities and are located at different positions. Each UAV should be assigned an attack task before the mission starts. Due to uncertain information, many criteria values essential to task assignment were random or fuzzy, and the weights of criteria were not precisely known. In this study, a novel task assignment approach based on stochastic Multicriteria acceptability analysis (SMAA) method was proposed to address this problem. The uncertainties in the criteria were analyzed, and a task assignment procedure was designed. The results of simulation experiments show that the proposed approach is useful for finding a satisfactory assignment under severe uncertain circumstances.