摘要
在单操作员监督控制多无人机进行搜索任务的场景下,为解决操作员的静态注意力分配问题,建立基于任务排序的静态注意力分配模型,目的是将合适的任务在合适的时间分配给操作员处理,实现任务的综合回报最大化。该模型对静态任务队列进行排序,同时设定每一个任务的处理时长和任务执行后操作员的休息时长。采用MATLAB仿真实验验证,利用动态规划和免疫算法进行求解。实验结果表明,在静态任务队列的注意力分配中此模型获得的综合回报,大于基于先进先出原则的注意力分配方法获得的综合回报。
In order to solve the static attention allocation problem( AAP) in the situation where a singleoperator manages multi-unmanned aerial vehicles( SOMU) and the UAVs are assigned to perform search tasks. A task scheduling-based model for the AAP of static SOMU operator is established. The aim is to allocate the proper task to an operator and maximize the integrated return. The proposed model is used to schedule the tasks in the static task queue and set the work and rest times for each task simultaneously.The proposed model is validated in MATLAB simulation environment,and the immune algorithm and dynamic programming algorithm are used to solve the model. Based on the simulation results,it was found that the integrated return obtained from the model is greater than that of the model based on first-in-firstout in static task queue.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2017年第S1期226-231,共6页
Acta Armamentarii
关键词
兵器科学与技术
多无人机
单操作员
静态任务队列
注意力分配
任务排序
ordnance science and technology
multi-unmanned aerial vehicle
single-operator
static task queue
attention allocation
task scheduling
