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Energy-Efficient Velocity Control for Massive Numbers of Rotary-Wing UAVs: A Mean Field Game Approach

机译:用于大量旋翼无人机的节能速度控制:平均场比赛方法

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When a disaster happens in a metropolitan area, wireless communication systems in the area are highly affected, degrading the efficiency of the search and rescue (SAR) mission. An emergency wireless network must be deployed quickly and efficiently to preserve human lives. Teams of low-altitude rotary-wing unmanned aerial vehicles (UAVs) are useful as on-demand temporal wireless networks because they are generally faster to deploy, flexible to reconfigure, and able to provide good communication services with short line-of-sight links. However, rotary-wing UAVs' limited on-board batteries require that they need to recharge and reconfigure frequently during a mission. Therefore, we formulate the velocity control problem for massive numbers of rotary-wing UAVs as a Schrödinger bridge problem which can describe the frequent reconfiguration of UAVs. Then we transform it into a mean field game and solve it with the G-prox primal dual hybrid gradient (PDHG) method. Finally, we show the efficiency of our algorithm and analyze the influence of wind dynamics with numerical results.
机译:当灾难大城市地区发生,区域内的无线通信系统的高度影响,降低了搜索与援救(SAR)任务的效率。紧急无线网络必须快速部署和高效维护人的生命。作为点播时间无线网络,因为它们通常部署更快速,灵活地重新配置,并能为用户提供短线的视距链路良好的通信服务低空旋翼无人飞行器(UAV)的球队是有用的。然而,旋转翼无人机限制车载电池要求他们经常在特派团需要补给和重新配置。因此,我们制定的速度控制问题进行旋转翼无人机的庞大的数字作为薛定谔桥问题可以描述无人机频繁的重新配置。然后,我们将其转化为平均场游戏,并与G-PROX原始二元杂交梯度(PDHG)方法解决这个问题。最后,我们将展示我们的算法的效率和分析风动态的和数值结果的影响。

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