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Completion Time Minimization for Multi-UAV Information Collection via Trajectory Planning

机译:通过轨迹规划完成多UAV信息收集的完成时间最小化

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Unmanned Aerial Vehicles (UAVs) are widely used as mobile information collectors for sensors to prolong the network time in Wireless Sensor Networks (WSNs) due to their flexible deployment, high mobility, and low cost. This paper focuses on the scenario where rotary-wing UAVs complete information collection mission cooperatively. For the first time, we study the problem of minimizing the mission completion time for a multi-UAV system in a monitoring scenario when considering the information collection quality. The mission completion time includes flying time and hovering time. By optimizing the trajectories of all UAVs, we minimize the mission completion time while ensuring that the information of each sensor is collected. This problem can be formulated as a mixed-integer non-convex one which has been proved to be NP-hard. To solve the formulated problem, we first propose a hovering point selection algorithm to select appropriate hovering points where the UAVs can sequentially collect the information from multiple sensors. We model this problem as a BS coverage problem with the information collection quality in consideration. Then, we use a min-max cycle cover algorithm to assign these hovering points and get the trajectory of each UAV. Finally, with the obtained UAVs trajectories, we further consider the UAVs can also collect information when flying and optimize the time allocations. The performance of our algorithm is verified by simulations, which show that the mission completion time is minimum compared with state-of-the-art algorithms.
机译:无人驾驶飞行器(无人机)广泛用作传感器的移动信息收集器,以延长无线传感器网络(WSNS)的网络时间,因为它们的灵活部署,高移动性和低成本。本文重点介绍旋翼无人机完整信息采集任务的场景。我们首次研究了在考虑信息收集质量时在监视方案中最小化多UAV系统的任务完成时间的问题。任务完成时间包括飞行时间和徘徊时间。通过优化所有无人机的轨迹,我们最小化任务完成时间,同时确保收集每个传感器的信息。该问题可以作为混合整数非凸起的问题被制定为已被证明是NP-HARD的。为了解决配制的问题,我们首先提出了一种悬停点选择算法来选择适当的悬停点,其中UAV可以顺序地从多个传感器中收集信息。考虑到信息收集质量,我们将此问题模拟了该问题。然后,我们使用MIN-MAX周期封面算法来分配这些悬停点并获取每个UAV的轨迹。最后,通过获得的无人机轨迹,我们进一步考虑在飞行时可以收集信息并优化时间分配。通过模拟验证了我们算法的性能,表明与最先进的算法相比,任务完成时间最小。

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