THE ROUTES OF UNMANNED AERIAL VEHICLE PLANNING METHODS ONTOLOGY

O. Chumak, M. Dudko, O. Dmitriiev
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Abstract

The article analyzes modern methods of the route of unmanned aerial vehicles (UAVs) planning. An ontology for the routes of the UAVs group planning algorithms classification has been developed, which includes two elements: global planning and local planning. The article notes that the purpose of UAV flight routes planning is the optimal (rational) solution of specific tasks under appropriate weather conditions and taking into account other factors of the external environment. According to the premise of taking into account a significant number of constraints, the objective function of planning is to reach each UAV from the group to the end point (mission point). Planning the UAVs group route is a complex task of its multi-criteria optimization and solution in the presence of constraints. With the increase in the UAVs number, the analytical space of the route planning task will grow exponentially. The existing methods of planning the of the UAVs group movement route have a number of disadvantages, therefore, the development of a comprehensive method that reduces computational requirements, saves time, allows to plan routes in real time, and is also more effective from the group's mission performance point of view. The article defines the requirements for the UAVs group routes planning promising methods: complex modeling of many factors of the external environment influence; planning in real time; integration of planning methods. Combining the characteristics of heuristic algorithms and machine learning methods also allows you to obtain complex methods that have a higher adaptability to the conditions of the external environment and expand the range of applications.
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无人驾驶飞行器路线规划方法本体论
文章分析了无人驾驶飞行器(UAVs)路线规划的现代方法。文章建立了无人飞行器航线分组规划算法分类本体论,其中包括两个要素:全局规划和局部规划。文章指出,无人机飞行路线规划的目的是在适当的天气条件下,考虑到外部环境的其他因素,为特定任务提供最优(合理)解决方案。在考虑大量约束条件的前提下,规划的目标函数是将每架无人机从组群中到达终点(任务点)。无人机群路线规划是一项复杂的任务,需要在存在约束条件的情况下对其进行多标准优化和求解。随着无人机数量的增加,路线规划任务的分析空间将呈指数级增长。现有的无人机群移动路线规划方法存在诸多弊端,因此需要开发一种综合方法,以降低计算要求、节省时间、实时规划路线,并且从无人机群的任务性能角度来看更加有效。文章定义了对无人机群航线规划可行方法的要求:外部环境诸多影响因素的复杂建模;实时规划;规划方法的集成。结合启发式算法和机器学习方法的特点,还可以获得对外部环境条件适应性更强的复杂方法,扩大应用范围。
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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