Statement of the Problem of Complete Set of UAV Group on the Basis of Models of Granular Calculations and Fuzzy Logic

V. Korolyov, M. Ogurtsov, A. Khodzinsky
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引用次数: 1

Abstract

Introduction. The increase in the number of heterogeneous groups of UAVs that jointly perform aerial photography missions generates a large amount of poorly structured information: videos, photos, telemetry records, navigation data. To build intelligent databases from unstructured information sources from UAV groups, granular computational approaches are proposed. These approaches are the basis for the application of Big Data technologies and artificial intelligence to increase situational awareness or commercial value of knowledge gained from the data flow from UAV groups. The purpose of the article. Develop new models for assessing the quality of video data from UAVs, approaches to equipping heterogeneous groups of UAVs and indicators for assessing its tactical and technical characteristics as a team. Results. The success of UAV group mission planning is based on the forecast of quantitative and qualitative indicators of the received video data. For this purpose, a model for forecasting the quality of the obtained aerial photographs based on the data on the speed, height of the UAV and the angle of the video camera is proposed. The model is based on the development of the theory of fuzzy sets of the first and second types. An example of the implementation of the model in the system of computer mathematics MatLab 2020b is given. Based on the analysis of a number of works on UAV classification and the proposed model of image quality, the method of equipment for the UAV group and the choice of UAV types are built, as well as the content of the combinatorial optimization problem based on the classic backpack problem. An example of calculations of tactical and technical characteristics for the Ukrainian UAV "Spectator" of Meridian ltd. is given. Conclusions. A new model for assessing the quality of aerial photography images based on fuzzy logic has been developed. The method of staffing UAV groups is proposed. Keywords: Fuzzy logic, granular calculations, UAV equipment, heterogeneous groups, computer simulation.
基于粒度计算和模糊逻辑模型的无人机机群成套问题的表述
介绍联合执行航空摄影任务的异构无人机组数量的增加产生了大量结构不良的信息:视频、照片、遥测记录、导航数据。为了利用无人机群组的非结构化信息源建立智能数据库,提出了细粒度计算方法。这些方法是应用大数据技术和人工智能的基础,以提高无人机小组从数据流中获得的知识的态势感知或商业价值。文章的目的。开发用于评估无人机视频数据质量的新模型,为异构无人机组配备设备的方法,以及作为一个团队评估其战术和技术特征的指标。后果无人机群任务规划的成功是基于对接收到的视频数据的定量和定性指标的预测。为此,提出了一种基于无人机速度、高度和摄像机角度数据预测所获得航空照片质量的模型。该模型是基于第一类和第二类模糊集理论的发展。给出了该模型在MatLab 2020b计算机数学系统中的实现实例。在分析了大量无人机分类工作和所提出的图像质量模型的基础上,建立了无人机机群的装备方法和无人机类型的选择,以及基于经典背包问题的组合优化问题的内容。给出了有限公司乌克兰无人机“旁观者”战术技术特性计算实例。结论。提出了一种新的基于模糊逻辑的航空摄影图像质量评估模型。提出了无人机机群的人员配置方法。关键词:模糊逻辑,粒度计算,无人机设备,异构组,计算机模拟。
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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