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A Framework and Analysis for Cooperative Search Using UAV Swarms

机译:无人机群协同搜索的框架与分析

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We design and analyze the performance of cooperative search strategies for unmanned aerial vehicles (UAVs) searching for moving, possibly evading, targets in a hazardous environment. Rather than engaging in independent sensing missions, the sensing agents (UAVs with sensors) "work together" by arranging themselves into a flight configuration that optimizes their integrated sensing capability. If a UAV is shot down by enemy fire, the team adapts by reconfiguring its topology to optimally continue the mission with the surviving assets. We present a cooperative search methodology that integrates the multiple agents into an advantageous formation that distinctively enhances the sensing and detection operations of the system while minimizing the transmission of excessive control information for adaptation of the team's topology. After analyzing our strategy to determine the performance tradeoff between search time and number of UAVs employed, we present an algorithm that selects the minimum number of UAVs to deploy in order to meet a targeted search time within probabilistic guarantees.
机译:我们设计和分析了在危险环境中搜索移动目标(可能逃避目标)的无人机的协作搜索策略的性能。而不是执行独立的传感任务,传感代理(带有传感器的UAV)通过将自己布置成优化其综合传感能力的飞行配置来“协同工作”。如果一架无人机被敌方火力击落,则该团队将对其拓扑结构进行重新配置,以利用剩余的资产以最佳方式继续执行任务。我们提出了一种协作搜索方法,该方法将多个代理集成到一个有利的形式中,该形式可以显着增强系统的感测和检测操作,同时最大程度地减少过多的信息传递以适应团队的拓扑结构。在分析了确定搜索时间与所用无人机数量之间性能折衷的策略之后,我们提出了一种算法,该算法选择要部署的最小无人机数量,以便在概率保证内满足目标搜索时间。

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