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Search Strategies for Multiple UAV Search and Destroy Missions

机译:多种无人机搜索和摧毁任务的搜索策略

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摘要

Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.
机译:部署了多架无人机,以在边界区域执行搜索和摧毁任务。无人飞行器的传感器范围有限,可以携带有限的资源,使用时资源会减少。无人机执行搜索任务以检测目标。当检测到需要完全摧毁不同类型和数量资源的目标时,就会组成一个被称为联盟的无人机小组来攻击目标。联盟成员必须修改其路线以攻击目标,在此过程中,搜索任务受到破坏,因为搜索任务和破坏任务被耦合。任务的执行取决于搜索和任务分配策略。因此,对于给定的任务分配策略,我们需要设计有效的搜索策略。在本文中,我们提出了三种不同的搜索策略:随机搜索策略,基于车道的搜索策略和基于网格的搜索策略,并通过蒙特卡洛模拟分析其性能。结果表明,基于网格的搜索策略执行效果最佳,但信息开销较高。

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