Abstract

The multicriteria task of preflight and operational planning of group actions of unmanned aerial vehicles (UAVs), taking into account the required service schedule, is considered. A minimax criterion for the operational planning of group actions when the dynamic situation changes is proposed. The shape of the expert system for controlling the duration of observation during the search and detection of ground objects is formed. The obtained results of assessing the quality of the solution to the subproblem of neural network recognition of mobile objects based on deep learning confirm the effectiveness of the proposed approach in monitoring the controlled area.

中文翻译：

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无人机在指定区域观察地面移动物体的群行动智能规划系统

摘要

考虑到所需的服务时间表，考虑了无人机 (UAV) 群体行动的飞行前和作战计划的多标准任务。提出了动态情况变化时群体行动行动规划的极小极大准则。形成了在地物搜索和检测过程中控制观测时长的专家系统的形态。对基于深度学习的移动物体神经网络识别子问题解的质量评估结果证实了所提出的方法在监控受控区域方面的有效性。