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Agent-based Control for Multi-UAV Information Collection

机译:基于代理的多无人机信息收集控制

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Multi-agent coordination and planning techniques play a fundamental role in designing control systems for autonomous multi-UAV-based information collection. The most important categories of information collection are exploration, surveillance, search and tracking. We introduce each category of information collection and then focus on a specific problem - multi-UAV-based surveillance in complex environments where sensor occlusions can occur due to high buildings and other obstacles in the target area. We formalize the problem and propose a solution as a decomposition of the problem in two subproblems: the problem of single-area surveillance and the problem of allocating UAVs to multiple areas. We present and compare several algorithms for the subproblems and prove their optimality. Finally, we empirically evaluate the performance of all algorithms on a realistic simulation of aerial surveillance, built using the AGENTFLYframework, and compare it to theoretical estimates.
机译:多主体协调和计划技术在设计用于基于多无人机的自主信息收集的控制系统中起着基本作用。信息收集的最重要类别是探索,监视,搜索和跟踪。我们介绍了每种类型的信息收集,然后重点介绍了一个特定的问题-在复杂环境中基于多UAV的监视,在该环境中,由于目标区域中的高层建筑物和其他障碍物而可能发生传感器阻塞。我们将问题形式化,并提出解决方案,将其分解为两个子问题:单区域监视问题和将无人机分配到多个区域的问题。我们提出并比较了子问题的几种算法,并证明了它们的最优性。最后,我们在使用AGENTFLY框架构建的实际空中监视仿真中,以经验方式评估所有算法的性能,并将其与理论估算值进行比较。

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