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On-board multi-objective mission planning for Unmanned Aerial Vehicles

机译:无人机的机载多目标任务计划

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A system for automated mission planning is presented with a view to operate Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). This paper describes methods for modelling decision variables, for enroute flight planning under Visual Flight Rules (VFR). For demonstration purposes, the task of delivering a medical package to a remote location was chosen. Decision variables include fuel consumption, flight time, wind and weather conditions, terrain elevation, airspace classification and the flight trajectories of other aircraft. The decision variables are transformed, using a Multi-Criteria Decision Making (MCDM) cost function, into a single cost value for a grid-based search algorithm (e.g. A*). It is shown that the proposed system provides a means for fast, autonomous generation of near-optimal flight plans, which in turn are a key enabler in the operation of UAVs in the NAS.
机译:提出了一种用于自动任务计划的系统,目的是在国家空域系统(NAS)中操作无人飞行器(UAV)。本文介绍了为可视化飞行规则(VFR)下的航线飞行计划建模决策变量的方法。出于演示目的,选择了将医疗包裹运送到远程位置的任务。决策变量包括油耗,飞行时间,风和天气状况,地形标高,空域分类以及其他飞机的飞行轨迹。使用多准则决策(MCDM)成本函数将决策变量转换为基于网格的搜索算法(例如A *)的单个成本值。结果表明,所提出的系统提供了一种快速,自动生成接近最佳飞行计划的方法,而这又是NAS中无人机运行的关键推动力。

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