
基于状态转移的UAV单机侦察任务调度策略研究
Tasks scheduling policy based on state transition for single UAV reconnaissance
针对不确定环境中侦察无人机执行多任务时不同的任务调度顺序对代价和收益的影响, 根据多任务执行过程的特征, 建立了任务执行过程的状态转移模型. 通过对模型推导获得了一个最优性判据, 根据该判据对任务进行降序排列能够得到最优调度. 仿真实验结果证明了文中所提调度策略的最优性, 将文中所提策略产生的表调度算法与遗传算法和穷举搜索进行实验对比, 实验结果与理论推导一致, 说明了文中所提策略的最优性和高效性.
It is well-known that different scheduling orders for UAV performing multitask will result in different income. In allusion to this, this paper proposes a state transition tasks scheduling model based on the features of the task implemented. Then we deduce the cost and income of the task scheduling for acquiring an optimality criterion whose descending order decides the optimal scheduling sequence. After that, the optimality of the policy is proved by simulation and we compare our algorithm with exhaust search and genetic algorithm, which shows that the theoretic result is consistent with.
无人机 / 任务调度 / 状态转移 / 遗传算法 {{custom_keyword}} /
unmanned aerial vehicles / task scheduling / state transition / genetic algorithm {{custom_keyword}} /
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国家高技术研究发展计划(863计划)(2011AA010106)
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