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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">izvestswsu</journal-id><journal-title-group><journal-title xml:lang="ru">Известия Юго-Западного государственного университета</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the Southwest State University</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2223-1560</issn><issn pub-type="epub">2686-6757</issn><publisher><publisher-name>ЮЗГУ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21869/2223-1560-2024-28-4-8-20</article-id><article-id custom-type="elpub" pub-id-type="custom">izvestswsu-1368</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Машиностроение и машиноведение</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Mechanical engineering and machine science</subject></subj-group></article-categories><title-group><article-title>Моделирование процесса автономной посадки БпЛА-квадрокоптера на движущуюся платформу с использованием инфракрасной оптической системы</article-title><trans-title-group xml:lang="en"><trans-title>Modeling the process of autonomous landing of a uav quadcopter on a moving platform using an infrared optical system</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0007-6998-5687</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Аникин</surname><given-names>Д. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Anikin</surname><given-names>D. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Дмитрий Андреевич Аникин, младший научный сотрудник</p><p>лаборатория автономных робототехнических систем</p><p>199178; 14 линия В.О., д. 39; Санкт-Петербург</p></bio><bio xml:lang="en"><p>Dmitry A. Anikin, Junior Researcher</p><p>Laboratory of Autonomous Robotic Systems</p><p>199178; 39, 14th Line; St. Petersburg</p></bio><email xlink:type="simple">anikin.d@iias.spb.su</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1851-2699</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Савельев</surname><given-names>А. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Saveliev</surname><given-names>A. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Антон Игоревич Савельев, старший научный сотрудник</p><p>лаборатория автономных робототехнических систем</p><p>199178; 14 линия В.О., д. 39; Санкт-Петербург</p></bio><bio xml:lang="en"><p>Anton I. Saveliev, Senior Researcher</p><p>Laboratory of Laboratory of Autonomous Robotic Systems</p><p>199178; 39, 14th Line; St. Petersburg</p></bio><email xlink:type="simple">saveliev@iias.spb.su</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Санкт-Петербургский Федеральный исследовательский центр Российской академии наук, Санкт-Петербургский институт информатики и автоматизации Российской академии наук</institution></aff><aff xml:lang="en"><institution>St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>07</day><month>04</month><year>2025</year></pub-date><volume>28</volume><issue>4</issue><fpage>8</fpage><lpage>20</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Аникин Д.А., Савельев А.И., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Аникин Д.А., Савельев А.И.</copyright-holder><copyright-holder xml:lang="en">Anikin D.A., Saveliev A.I.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://izvestswsu.elpub.ru/jour/article/view/1368">https://izvestswsu.elpub.ru/jour/article/view/1368</self-uri><abstract><sec><title>   Цель исследования</title><p>   Цель исследования. Оценка эффективности работы системы автоматической посадки БпЛА на подвижную платформу с использованием инфракрасного маяка на основе критериев точности посадки и успешность маневра при различных высотах.</p></sec><sec><title>   Методы</title><p>   Методы. Моделирование процесса движения сложного объекта (БпЛА) в среде Gazebo с использованием экосистемы ROS. Позиционирование БпЛА основано на математической модели инфракрасного маяка, состоящего из четырех пар излучателей. Алгоритм посадки включает адаптивные ПИД-регуляторы для координат X и Y и логполиномиальный регулятор для обеспечения снижения аппарата по оси Z.</p></sec><sec><title>   Результаты</title><p>   Результаты. Тестирование посадки БпЛА проводилось 50 раз с высот 5 м, 10 м и 15 м . На высоте 5 м время посадки составило 9,04 сек (разброс 0,504 сек), ошибка – 0,18 м (разброс 0,035 м), успешность – 100 %. На 10 м время увеличилось до 19,17 сек (разброс 1,78 сек), ошибка – 0,19 м (разброс 0,036 м), успешность осталась 100 %. На 15 м время возросло до 40,45 сек (разброс 5,502 сек), ошибка – 0,21 м (разброс 0,046 м), распределение данных стало шире, появились выбросы, успешность снизилась до 92 %, что связано с потерями сигналов, их затуханием и необходимостью коррекции траектории. Увеличение высоты тестирования процесса посадки нецелесообразно из-за снижения вероятности успешной посадки.</p></sec><sec><title>   Заключение</title><p>   Заключение. Исследование показало, что система инфракрасного маяка эффективно работает для посадки БпЛА на подвижную платформу на высотах до 10 м, обеспечивая необходимую стабильность и точность. При высотах свыше 10 м возникают проблемы с потерей сигналов, увеличением времени посадки и ошибками, что требует улучшений для обеспечения надежности посадки.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>   Purpose of research</title><p>   Purpose of research. Evaluation of the effectiveness of the UAV automatic landing system on a mobile platform using an infrared beacon based on criteria for landing accuracy and maneuver success at various altitudes.</p></sec><sec><title>   Methods</title><p>   Methods. Modeling the process of movement of a complex object (UAV) in the Gazebo environment using the ROS ecosystem. The positioning of the UAV is based on a mathematical model of an infrared beacon consisting of four pairs of emitters. The landing algorithm includes adaptive PID controllers for the X and Y coordinates and a logo polynomial controller to ensure the descent of the UAV along the Z axis.</p></sec><sec><title>   Results</title><p>   Results. The UAV landing was tested 50 times from heights of 5 m, 10 m and 15 m. At a height of 5 m, the landing time was 9.04 seconds (0.504 sec deviation), the error was 0.18 m (0.035 m deviation), the success rate was 100  %. At 10 m, the time increased to 19.17 seconds (1.78 sec deviation), the error was 0.19 m (0.036 m deviation), the success rate remained 100 %. At 15 m, the time increased to 40.45 seconds (5.502 seconds deviation), the error was 0.21 m (0.046 m deviation), the data distribution became wider, outliers appeared, the success rate decreased to 92 %, which is due to signal losses, their attenuation and the need to correct the trajectory. Increasing the height of the landing process testing is impractical due to a decrease in the probability of a successful landing.</p></sec><sec><title>   Conclusion</title><p>   Conclusion. The study showed that the infrared beacon system works effectively for landing UAVs on a mobile platform at altitudes up to 10 m, providing the necessary stability and accuracy. At altitudes above 10 m, problems arise with loss of signals, increased landing time and errors, which require improvements to ensure the reliability of landing.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>автономная посадка</kwd><kwd>БпЛА</kwd><kwd>имитационное моделирование</kwd><kwd>математические модели</kwd><kwd>навигация</kwd><kwd>инфракрасный маяк</kwd></kwd-group><kwd-group xml:lang="en"><kwd>autonomous landing</kwd><kwd>UAV</kwd><kwd>simulation modeling</kwd><kwd>mathematical models</kwd><kwd>navigation</kwd><kwd>infrared beacon</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Li X., et al. Drone-aided delivery methods, challenge, and the future : A methodological review // Drones. 2023. Vol. 7, №. 3. P. 191.</mixed-citation><mixed-citation xml:lang="en">Li X., et al. Drone-aided delivery methods, challenge, and the future : A methodological review. 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