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A multi-objective approach for unmanned aerial vehicle routing problem with soft time windows constraints

机译:具有软时间窗约束的无人机航路问题的多目标方法

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Aerial robotics can be very useful to perform complex tasks in a distributed and cooperative fashion, such as localization of targets and search of point of interests (Pols). In this work, we propose a distributed system of autonomous Unmanned Aerial Vehicles (UAVs), able to self-coordinate and cooperate in order to ensure both spatial and temporal coverage of specific time and spatial varying Pols. In particular, we consider an UAVs system able to solve distributed dynamic scheduling problems, since each device is required to move towards a certain position in a certain time. We give a mathematical formulation of the problem as a multi-criteria optimization model, in which the total distances traveled by the UAVs (to be minimized), the customer satisfaction (to be maximized) and the number of used UAVs (to be minimized) are considered simultaneously. A dynamic variant of the basic optimization model, defined by considering the rolling horizon concept, is shown. We introduce a case study as an application scenario, where sport actions of a football match are filmed through a distributed UAVs system. The customer satisfaction and the traveled distance are used as performance parameters to evaluate the proposed approaches on the considered scenario.
机译:空中机器人技术对于以分布式和协作方式执行复杂任务非常有用,例如目标的定位和兴趣点(Pol)的搜索。在这项工作中,我们提出了一种分布式自主无人飞行器(UAV)系统,该系统能够进行自我协调和协作,以确保特定时间和空间变化Pol的时空覆盖范围。特别地,我们考虑一种能够解决分布式动态调度问题的无人机系统,因为要求每个设备在特定时间内移至特定位置。我们将问题的数学公式表示为多准则优化模型,其中,无人机行驶的总距离(要最小化),客户满意度(要最大化)和二手无人机的数量(要最小化)同时考虑。显示了通过考虑滚动视野概念定义的基本优化模型的动态变体。我们介绍一个案例研究作为应用场景,其中足球比赛的运动行为通过分布式无人机系统进行拍摄。客户满意度和行进距离用作性能参数,以在考虑的情况下评估建议的方法。

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