Power Management for Noise Aware Path Planning of Hybrid UAVs

Drew Scott, S. Manyam, D. Casbeer, Manish Kumar, Michael Rothenberger, Isaac E. Weintraub
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引用次数: 1

Abstract

Here we consider the problem of path planning for a hybrid fuel Unmanned Aerial Vehicle (UAV), equipped with both a battery and gasoline generator as two sources of energy. Routing the vehicle while considering this setup adds fuel constraints in addition to requiring the power source state to be specified along each edge along the path. We further add noise restrictions to the problem where certain edges (corresponding to certain portions of the path) have the restriction that the gasoline generator cannot be run. A solution to this path planning problem entails both a sequence of nodes, being the plain path the vehicle travels, and a sequence of values specifying the power source along each edge in the path. There is no work in the current literature regarding such a problem, with little at all concerning general planning or routing for hybrid fuel UAVs. Here, hybrid fuel UAV routing problem with noise restrictions is presented. The problem is first formulated as an Mixed Integer Linear Program. Then a dynamic programming algorithm is presented to solve the problem exactly. This algorithm is then compared to a branch-and-cut based method in terms of computational times for a variety of problem sizes. A case study is presented, using a graph which location data from an area surrounding an airport to produce goal nodes and noise restrictions to display the problem itself as well as the performance of the dynamic programming algorithm in a realistic scenario for this problem.
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混合动力无人机噪声感知路径规划的电源管理
本文研究了一种混合燃料无人机(UAV)的路径规划问题,该无人机同时配备了电池和汽油发电机作为两种能源。在考虑这种设置的情况下,车辆的路线除了需要在路径的每个边缘指定电源状态外,还增加了燃料限制。在某些边缘(对应于路径的某些部分)限制汽油发电机不能运行的情况下,我们进一步增加了噪声限制。该路径规划问题的解决方案需要一个节点序列(即车辆行驶的普通路径)和一个值序列(指定路径中每条边的电源)。在目前的文献中没有关于这样一个问题的工作,几乎没有关于混合燃料无人机的总体规划或路由。研究了具有噪声约束的混合燃料无人机路由问题。该问题首先被表述为一个混合整数线性规划。在此基础上,提出了一种动态规划算法来精确求解这一问题。然后,就各种问题大小的计算时间而言,将该算法与基于分支和切割的方法进行比较。给出了一个案例研究,利用机场周围区域的位置数据生成目标节点和噪声限制的图来显示问题本身以及动态规划算法在该问题的实际场景中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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