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Multiple UAV teams for multiple tasks

机译:多个无人机团队执行多项任务

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摘要

In a search and prosecute mission, multiple heterogeneous unmanned aerial vehicles UAVs that carry different resources need to perform the classify, prosecute and battle damage assessment (BDA) tasks on targets sequentially. Depending on the target resource requirement, it may be necessary to deploy a coalition of UAVs to perform the action. In this paper, we propose coalition formation algorithms that have low computational overhead to determine coalitions for the prosecute and the BDA tasks. We also develop a simultaneous strike mechanism based on Dubins curves for the UAVs to prosecute the target simultaneously. Monte-Carlo simulation results are presented to show how the algorithms work and the effect of increasing the number of BDA tasks on the mission performance.
机译:在搜索和起诉任务中,携带不同资源的多台异构无人飞行器无人机需要按顺序对目标执行分类,起诉和战损评估(BDA)任务。根据目标资源要求,可能有必要部署无人飞行器联盟来执行该操作。在本文中,我们提出了具有较低计算开销的联盟形成算法来确定起诉和BDA任务的联盟。我们还开发了一种基于杜宾斯曲线的同时打击机制,用于无人机同时起诉目标。提出了蒙特卡洛仿真结果,以显示算法如何工作以及增加BDA任务数量对任务性能的影响。

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