Intelligent mobile object monitoring by unmanned aerial vehicles

被引：3

作者：

Knyaz, Vladimir ^{[1
]}

Zheltov, Sergey ^{[1
]}

Lebedev, Georgy ^{[2
]}

Mikhailin, Denis ^{[2
]}

Goncharenko, Vladimir ^{[2
]}

机构：

[1] Moscow Inst Phys & Technol, State Res Inst Aviat Syst, Machine Vis Dept, Moscow, Russia

[2] Moscow Inst Aviat Technol, Control Syst Dept, Moscow, Russia

来源：

PROCEEDINGS OF 18TH INTERNATIONAL CONFERENCE ON SMART TECHNOLOGIES (IEEE EUROCON 2019) | 2019年

基金：

俄罗斯基础研究基金会;

关键词：

Mission planning; genetic algorithm; object recognition; convolutional neural network; unmanned aerial vehicle; fuzzy logic;

D O I：

10.1109/EUROCON.2019.8861575

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The progress in technical characteristics of unmanned aerial vehicles (UAV) creates a background for their expanding use in applications where human capabilities are limited. Such applications as object monitoring in hard-to-get environment, extremal sport rally, rescue operation, require object surveillance in large regions and complex conditions. To provide high level of UAV autonomy three tasks should be solved: intelligent mission planning, object recognition and on the fly mission modifying according to changing conditions. The paper presents algorithms for these tasks based on artificial intelligence techniques.

引用

页数：6

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