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Guaranteed Search With Large Teams of Unmanned Aerial Vehicles

机译:保证使用无人驾驶飞行器的大队搜索

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We consider the problem of computing trajectories for a team of of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments to guarantee the detection of any evading target. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are computed from the motion of these sweep lines. Low cost coordination strategies of the UAV sweep lines are computed in 2D and simply-connected polygonal environments and then converted to strategies capable of clearing multiply-connected 2.5D environments. We present simulation experiments with maps of real and artificial environments and demonstrate the execution of strategies with simulated quadrotors using the Robot Operating System (ROS) framework. The algorithms used for the experiments are made available on a public repository.
机译:我们考虑在大型和复杂的2D和2.5D环境中协调无人驾驶飞行器(无人机)的协调团队的轨迹的问题,以保证任何逃避目标的检测。我们的方法是基于2D扫描线的协调,移动通过环境来清除所有污染,代表位于一个区域中的目标,从而检测所有目标。从这些扫描线的运动中计算无人机的轨迹。 UAV扫描线的低成本协调策略在2D和简单连接的多边形环境中计算,然后转换为能够清除乘法连接的2.5D环境的策略。我们在实际和人造环境的地图上呈现模拟实验,并展示使用机器人操作系统(ROS)框架的模拟四轮压积器的执行。用于实验的算法在公共存储库上提供。

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