<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<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">novtexmech</journal-id><journal-title-group><journal-title xml:lang="ru">Мехатроника, автоматизация, управление</journal-title><trans-title-group xml:lang="en"><trans-title>Mekhatronika, Avtomatizatsiya, Upravlenie</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1684-6427</issn><issn pub-type="epub">2619-1253</issn><publisher><publisher-name>Commercial Publisher «New Technologies»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17587/mau.22.634-643</article-id><article-id custom-type="elpub" pub-id-type="custom">novtexmech-1097</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>РОБОТЫ, МЕХАТРОНИКА И РОБОТОТЕХНИЧЕСКИЕ СИСТЕМЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ROBOT, MECHATRONICS AND ROBOTIC SYSTEMS</subject></subj-group></article-categories><title-group><article-title>Распределенная система локализации объектов в рабочей зоне модульного реконфигурируемого мобильного робота</article-title><trans-title-group xml:lang="en"><trans-title>Distributed System for Objects Localization in the Working Area of a Modular Reconﬁgurable Mobile Robot</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Волкова</surname><given-names>М. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Volkova</surname><given-names>M. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Старший преподаватель</p></bio><bio xml:lang="en"><p>Volkova Maria A. Senior Lecturer</p></bio><email xlink:type="simple">volkova_m@mirea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Романов</surname><given-names>А. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Romanov</surname><given-names>A. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кандидат технических наук, доцент</p></bio><bio xml:lang="en"><p>Associate Professor</p></bio><email xlink:type="simple">romanov@mirea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Романов</surname><given-names>М. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Romanov</surname><given-names>M. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Доктор технических наук, профессор</p></bio><bio xml:lang="en"><p>Director of the Institute of Cybernetics</p></bio><email xlink:type="simple">m_romanov@mirea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>МИРЭА — Российский технологический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>MIREA — Russian technological university</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>01</day><month>12</month><year>2021</year></pub-date><volume>22</volume><issue>12</issue><fpage>634</fpage><lpage>643</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Commercial Publisher «New Technologies», 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Commercial Publisher «New Technologies»</copyright-holder><copyright-holder xml:lang="en">Commercial Publisher «New Technologies»</copyright-holder><license xlink:href="https://mech.novtex.ru/jour/about/submissions#copyrightNotice" xlink:type="simple"><license-p>https://mech.novtex.ru/jour/about/submissions#copyrightNotice</license-p></license></permissions><self-uri xlink:href="https://mech.novtex.ru/jour/article/view/1097">https://mech.novtex.ru/jour/article/view/1097</self-uri><abstract><p>Предлагается новый подход к локализации объектов в рабочей зоне модульного реконфигурируемого робота (МРР), предполагающий установку роботом стационарных опорных измерительных пунктов (ОИП), состоящих из отделяемых от него модулей. В основе данного подхода лежит ранее предложенная авторами архитектура системы управления МРР и новый метод сопоставления информации о скорости и положении объектов, получаемой с различных сенсоров. Суть подхода состоит в следующем: прибыв в зону выполнения задачи, МРР выделяет из своего состава ОИП, содержащий источник питания, вычислительное устройство, беспроводной приемопередатчик и сенсор. ОИП осуществляют слежение за рабочей зоной с использованием разнородных датчиков (камер, дальномеров и т. д.), сегментацию объектов по получаемым измерениям и передачу этой информации на борт робота. Далее с использованием нового метода сопоставления информации о скорости и положении объектов происходит сопоставление измерений, полученных с различных сенсоров, что позволяет локализовать объекты даже в тех случаях, когда они не видны для части ОИП. Одним из ключевых преимуществ нового подхода является возможность его реализации в распределенной архитектуре МРР. Проведенные модельные экспериментальные исследования показали, что по критерию качества отслеживания Multiple Object Tracking Accuracy (MOTA) метод имеет оценку 86 %, что превосходит большинство известных аналогов, а динамическая ошибка локализации объектов в рабочей зоне 8Ѕ7 м с использованием двух камер и одного дальномера не превышает 10 см.</p></abstract><trans-abstract xml:lang="en"><p>The paper proposes a novel approach to the objects localization in the working area of a modular reconfigurable robot (MRR), which implies the installation of stationary monitoring points (SMP), consisting of detachable robot’s modules and in- stalled by robot itself. This approach is based on the architecture of the MRR control system previously proposed by the authors and a new method for comparing information about the speed and position obtained from various sensors. The key steps of the approach are following. Upon arriving in the target area, the MRR places SMPs, which consist of a power source, a computing device, a wireless transceiver and a sensor, detached from the robot. Then SMPs monitor the working area using different types of sensors (cameras, rangefinders, etc.), perform segmentation of the measured data and transfer this information to the robot. Further a sensor fusion is performed using a novel object tracking method, which makes it possible to localize target objects even in those cases when they are not visible by some of the SMPs. One of the key advantages of the new approach is a possibility of implementation in the distributed architecture of a MRR. The simulation results show that proposed method has Multiple Object Tracking Accuracy (MOTA) metric of 86 %, which is higher than the most of its analogues, while the estimated dynamic object localization error in a 8x7 m working area using 2 cameras and 1 rangefinder does not exceed 10 cm.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>реконфигурируемые роботы</kwd><kwd>локализация объектов</kwd><kwd>слежение за объектами</kwd><kwd>комплексирование сенсорной информации</kwd></kwd-group><kwd-group xml:lang="en"><kwd>reconfigurable robots</kwd><kwd>object localization</kwd><kwd>object tracking</kwd><kwd>sensor fusion</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 19-38-90301.</funding-statement><funding-statement xml:lang="en">The reported study was funded by RFBR, project number 19-38-90301.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Billard A., Kragic D. Trends and challenges in robot manipulation // Science. 2019. Vol. 364, N. 6446. P. eaat8414.</mixed-citation><mixed-citation xml:lang="en">Billard A., Kragic D. Trends and challenges in robot manipulation, Science, 2019, vol. 364, no. 6446, pp. eaat8414.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Yasuda Y. D. V., Martins L. E. G., Cappabianco F. A. M. Autonomous visual navigation for mobile robots: A systematic literature review // ACM Computing Surveys (CSUR). 2020. Vol. 53, N. 1. P. 1—34.</mixed-citation><mixed-citation xml:lang="en">Yasuda Y. D. V., Martins L. E. G., Cappabianco F. A. M. Autonomous visual navigation for mobile robots: A systematic literature review, ACM Computing Surveys (CSUR), 2020, vol. 53, no. 1, pp. 1—34.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Tolani V. et al. Visual navigation among humans with optimal control as a supervisor // IEEE Robotics and Automation Letters. 2021. Vol. 6, N. 2. P. 2288—2295.</mixed-citation><mixed-citation xml:lang="en">Tolani V. et al. Visual navigation among humans with optimal control as a supervisor, IEEE Robotics and Automation Letters, 2021, vol. 6, no. 2, pp. 2288—2295.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Payá L., Gil A., Reinoso O. A state-of-the-art review on mapping and localization of mobile robots using omnidirectional vision sensors // Journal of Sensors. 2017. Vol. 2017. P. 1—20.</mixed-citation><mixed-citation xml:lang="en">Payá L., Gil A., Reinoso O. A state-of-the-art review on mapping and localization of mobile robots using omnidirectional vision sensors, Journal of Sensors, 2017, vol. 2017, pp. 1—20.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Chen H. et al. Vision and laser fused SLAM in indoor environments with multi-robot system // Assembly Automation. 2019. Vol. 39, N. 2. P. 297—307.</mixed-citation><mixed-citation xml:lang="en">Chen H. et al. Vision and laser fused SLAM in indoor environments with multi-robot system, Assembly Automation, 2019, vol. 39, no. 2, pp. 297—307.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Tang B., Jiang L. Binocular stereovision omnidirectional motion handling robot // International Journal of Advanced Robotic Systems. 2020. Vol. 17, N. 3. P. 1729881420926852.</mixed-citation><mixed-citation xml:lang="en">Tang B., Jiang L. Binocular stereovision omnidirectional motion handling robot, International Journal of Advanced Robotic Systems, 2020, vol. 17, no. 3, pp. 1729881420926852.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Kuo C. Y. et al. Development of an immersive SLAMbased VR system for teleoperation of a mobile manipulator in an unknown environment // Computers in Industry. 2021. Vol. 132. P. 103502.</mixed-citation><mixed-citation xml:lang="en">Kuo C. Y. et al. Development of an immersive SLAM-based VR system for teleoperation of a mobile manipulator in an unknown environment, Computers in Industry, 2021, vol. 132, pp. 103502.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A. M. et al. A Navigation System for Intelligent Mobile Robots // 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2019. P. 652—656.</mixed-citation><mixed-citation xml:lang="en">Romanov A. M. et al. A Navigation System for Intelligent Mobile Robots, 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), IEEE, 2019, pp. 652—656.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Yang Y. et al. 3D multiview basketball players detection and localization based on probabilistic occupancy // 2018 Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2018. P. 1—8.</mixed-citation><mixed-citation xml:lang="en">Yang Y. et al. 3D multiview basketball players detection and localization based on probabilistic occupancy, 2018 Digital Image Computing: Techniques and Applications (DICTA), IEEE, 2018, pp. 1—8.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Егорцев М. В., Диане С. А. К., Кац Н. Д. Алгоритмическое обеспечение системы внешнего наблюдения и маршрутизации автономных мобильных роботов // Российский технологический журнал. 2021. Т. 9, № 3. С. 15—23.</mixed-citation><mixed-citation xml:lang="en">Egortsev M. V., Diane S. K., Kaz N. D. Algorithmic support of the system of external observation and routing of autonomous mobile robots, Russian Technological Journal, 2021, vol. 9, no. 3, pp. 15—23 (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Ben Y., Cengiz K. Research on Visual Orientation Guidance of Industrial Robot Based on CAD Model under Binocular Vision // Computer-Aided Design and Applications. 2022. Vol. 19. N. S2. P. 52—63.</mixed-citation><mixed-citation xml:lang="en">Ben Y., Cengiz K. Research on Visual Orientation Guidance of Industrial Robot Based on CAD Model under Binocular Vision, Computer-Aided Design and Applications, 2022, vol. 19, no. S2, pp. 52—63.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Srigrarom S. et al. Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification // 2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP). IEEE, 2021. P. 1—6.</mixed-citation><mixed-citation xml:lang="en">Srigrarom S. et al. Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification, 2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP), IEEE, 2021, pp. 1—6.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Park S. et al. Survey on Anti-Drone Systems: Components, Designs, and Challenges // IEEE Access. 2021. Vol. 9. P. 42635—42659.</mixed-citation><mixed-citation xml:lang="en">Park S. et al. Survey on Anti-Drone Systems: Components, Designs, and Challenges, IEEE Access, 2021, vol. 9, pp. 42635—42659.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Khalyasmaa A. I. et. al. Diagnostic system for OHL state assessment // 2015 International Siberian Conference on Control and Communications (SIBCON). IEEE, 2015. P. 1—5.</mixed-citation><mixed-citation xml:lang="en">Khalyasmaa A. I. et. al. Diagnostic system for OHL state assessment, 2015 International Siberian Conference on Control and Communications (SIBCON), IEEE, 2015, pp. 1—5.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Khalyasmaa A. I. et. al. Robotic intelligence laboratory for overhead transmission lines assessment // 2016 57th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). IEEE, 2016. P. 1—6.</mixed-citation><mixed-citation xml:lang="en">Khalyasmaa A. I. et. al. Robotic intelligence laboratory for overhead transmission lines assessment, 2016 57th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), IEEE, 2016, pp. 1—6.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Schuster M. J. et al. Distributed stereo vision-based 6D localization and mapping for multi-robot teams // Journal of Field Robotics. 2019. Vol. 36, N. 2. P. 305—332.</mixed-citation><mixed-citation xml:lang="en">Schuster M. J. et al. Distributed stereo vision-based 6D localization and mapping for multi-robot teams, Journal of Field Robotics, 2019, vol. 36, no. 2, pp. 305—332.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Андреев В. П., Подураев Ю. В. Функционально-модульный принцип построения гетерогенных мобильных роботов // Экстремальная робототехника. 2016. Т. 1, № 1. С. 39—49.</mixed-citation><mixed-citation xml:lang="en">Andreev V. P., Poduraev Yu. V. Functional-modular design of heterogeneous mobile robotic systems, Extreme Robotics, 2016, vol. 1, no. 1, pp. 39—49 (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A. M., Romanov M. P., Shestakov E. I. A novel architecture for control systems of modular reconfigurable robots // 2017 IEEE II International Conference on Control in Technical Systems (CTS). IEEE, 2017. P. 131—134.</mixed-citation><mixed-citation xml:lang="en">Romanov A. M., Romanov M. P., Shestakov E. I. A novel architecture for control systems of modular reconfigurable robots, 2017 IEEE II International Conference on Control in Technical Systems (CTS), IEEE, 2017, pp. 131—134.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Yao R. et al. Video object segmentation and tracking: A survey // ACM Transactions on Intelligent Systems and Technology (TIST). 2020. Vol. 11, N. 4. P. 1—47.</mixed-citation><mixed-citation xml:lang="en">Yao R. et al. Video object segmentation and tracking: A survey, ACM Transactions on Intelligent Systems and Technology (TIST), 2020, vol. 11, no. 4, pp. 1—47.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Li Y., Ibanez-Guzman J. Lidar for autonomous driving: The principles, challenges, and trends for automotive lidar and perception systems // IEEE Signal Processing Magazine. 2020. Vol. 37, N. 4. P. 50—61.</mixed-citation><mixed-citation xml:lang="en">Li Y., Ibanez-Guzman J. Lidar for autonomous driving: The principles, challenges, and trends for automotive lidar and perception systems, IEEE Signal Processing Magazine, 2020, vol. 37, no. 4, pp. 50—61.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Minaee S. et al. Image segmentation using deep learning: A survey //IEEE Transactions on Pattern Analysis and Machine Intelligence. 2021.</mixed-citation><mixed-citation xml:lang="en">Minaee S. et al. Image segmentation using deep learning: A survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Ariff S. A. M. et al. Exploratory Study of 3d Point Cloud Triangulation for Smart City Modelling and Visualization // The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. 2020. Vol. 44. P. 71—79.</mixed-citation><mixed-citation xml:lang="en">Ariff S. A. M. et al. Exploratory Study of 3d Point Cloud Triangulation for Smart City Modelling and Visualization, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020, vol. 44, pp. 71—79.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Álvarez H. et al. A Multi Camera and Multi Laser Calibration Method for 3D Reconstruction of Revolution Parts // Sensors. 2021. Vol. 21, N. 3. P. 765.</mixed-citation><mixed-citation xml:lang="en">Álvarez H. et al. A Multi Camera and Multi Laser Calibration Method for 3D Reconstruction of Revolution Parts, Sensors, 2021, vol. 21, no. 3, pp. 765.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Llamazares Á., Molinos E. J., Oca a M. Detection and tracking of moving obstacles (DATMO): a review // Robotica. 2020. Vol. 38, N. 5. P. 761—774.</mixed-citation><mixed-citation xml:lang="en">Llamazares Á., Molinos E. J., Oca@ña M. Detection and tracking of moving obstacles (DATMO): a review, Robotica, 2020, vol. 38, no. 5, pp. 761—774.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang Z. et al. Multiple target tracking based on multiple hypotheses tracking and modified ensemble Kalman filter in multi-sensor fusion // Sensors. 2019. Vol. 19, N. 14. P. 3118.</mixed-citation><mixed-citation xml:lang="en">Zhang Z. et al. Multiple target tracking based on multiple hypotheses tracking and modified ensemble Kalman filter in multi-sensor fusion, Sensors, 2019, vol. 19, no. 14, pp. 3118.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Sekii T. Robust, real-time 3d tracking of multiple objects with similar appearances // Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016. P. 4275—4283.</mixed-citation><mixed-citation xml:lang="en">Sekii T. Robust, real-time 3d tracking of multiple objects with similar appearances, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4275—4283.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Sun Q. et al. Multiple object tracking for yellow feather broilers based on foreground detection and deep learning // INMATEH-Agricultural Engineering. 2019. Vol. 58, N. 2.</mixed-citation><mixed-citation xml:lang="en">Sun Q. et al. Multiple object tracking for yellow feather broilers based on foreground detection and deep learning, INMATEHAgricultural Engineering, 2019, vol. 58, no. 2.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Мокшин В. В., Кирпичников А. П., Шарнин Л. М. Отслеживание объектов в видеопотоке по значимым признакам на основе фильтрации частиц // Вестник Казанского технологического университета. 2013. Vol. 16, N. 18. P. 306—310.</mixed-citation><mixed-citation xml:lang="en">Mokshin V. V., Kirpichnikov A. P., Sharnin L. M. Particle filtering-based objects tracking in a video stream using significant features, Vestnik Kazanskogo tehnologicheskogo universiteta, 2013, vol. 16, no. 18, pp. 297—303 (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Zhou J., Kwan C. Tracking of multiple pixel targets using multiple cameras // International Symposium on Neural Networks. Springer, Cham, 2018. P. 484—493.</mixed-citation><mixed-citation xml:lang="en">Zhou J., Kwan C. Tracking of multiple pixel targets using multiple cameras, International Symposium on Neural Networks, Springer, Cham, 2018, pp. 484—493.</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Eshel R., Moses Y. Homography based multiple camera detection and tracking of people in a dense crowd // 2008 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2008. P. 1—8.</mixed-citation><mixed-citation xml:lang="en">Eshel R., Moses Y. Homography based multiple camera detection and tracking of people in a dense crowd, 2008 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 2008, pp. 1—8.</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Teizer J., Caldas C. H., Haas C. T. Real-time threedimensional occupancy grid modeling for the detection and tracking of construction resources // Journal of Construction Engineering and Management. 2007. Vol. 133, N. 11. P. 880—888.</mixed-citation><mixed-citation xml:lang="en">Teizer J., Caldas C. H., Haas C. T. Real-time three-dimensional occupancy grid modeling for the detection and tracking of construction resources, Journal of Construction Engineering and Management, 2007, vol. 133, no. 11, pp. 880—888.</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Coué C. et al. Bayesian occupancy filtering for multitarget tracking: an automotive application // The International Journal of Robotics Research. 2006. Vol. 25, N. 1. P. 19—30.</mixed-citation><mixed-citation xml:lang="en">Coué C. et al. Bayesian occupancy filtering for multitarget tracking: an automotive application, The International Journal of Robotics Research, 2006, vol. 25, no. 1, pp. 19—30.</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Gindele T. et al. Bayesian occupancy grid filter for dynamic environments using prior map knowledge // 2009 IEEE Intelligent Vehicles Symposium. IEEE, 2009. P. 669—676.</mixed-citation><mixed-citation xml:lang="en">Gindele T. et al. Bayesian occupancy grid filter for dynamic environments using prior map knowledge, 2009 IEEE Intelligent Vehicles Symposium, IEEE, 2009, pp. 669—676.</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Nuss D., Yuan T., Krehl G., Stuebler M., Reuter S., Dietmayer K. Fusion of laser and radar sensor datawith a sequential Monte Carlo Bayesian occupancy filter // Proceedings of the 2015 IEEE Intelligent VehiclesSymposium (IV), Seoul, Korea, 28 June—1 July 2015. P. 1074—1081.</mixed-citation><mixed-citation xml:lang="en">Nuss D.,Yuan T.,Krehl G., Stuebler M., Reuter S., Dietmayer K. Fusion of laser and radar sensor datawith a sequential Monte Carlo Bayesian occupancy filter, Proceedings of the 2015 IEEE Intelligent VehiclesSymposium (IV), Seoul, Korea, 28 June—1 July 2015, pp. 1074—1081.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Taj M., Cavallaro A. Distributed and decentralized multicamera tracking // IEEE Signal Processing Magazine. 2011. Vol. 28, N. 3. P. 46—58.</mixed-citation><mixed-citation xml:lang="en">Taj M., Cavallaro A. Distributed and decentralized multicamera tracking, IEEE Signal Processing Magazine, 2011, vol. 28, no. 3, pp. 46—58.</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Taj M., Cavallaro A. Simultaneous Detection and Tracking with Multiple Cameras // Machine Learning for Computer Vision. Springer, Berlin, Heidelberg, 2013. С. 197—214.</mixed-citation><mixed-citation xml:lang="en">Taj M., Cavallaro A. Simultaneous Detection and Tracking with Multiple Cameras, Machine Learning for Computer Vision, Springer, Berlin, Heidelberg, 2013, pp. 197—214.</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Liang Q. et al. Multi-Player Tracking for Multi-View Sports Videos with Improved K-Shortest Path Algorithm // Applied Sciences. 2020. Vol. 10, N. 3. P. 864.</mixed-citation><mixed-citation xml:lang="en">Liang Q. et al. Multi-Player Tracking for Multi-View Sports Videos with Improved K-Shortest Path Algorithm, Applied Sciences, 2020, vol. 10, no. 3, pp. 864.</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A., Yashunskiy V., Chiu W.-Y. SABER: Modular Reconfigurable Robot for Industrial Applications // IEEE 17th International Conference on Automation Science and Engineering (CASE) 2021. 2021 (в печати).</mixed-citation><mixed-citation xml:lang="en">Romanov A., Yashunskiy V., Chiu W.-Y. SABER: Modular Reconfigurable Robot for Industrial Applications, IEEE 17th International Conference on Automation Science and Engineering (CASE). 2021, 2021 (in press).</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A. M., Mikheenko I. S. A novel approach for creating modular reconfigurable robots with distributed power system // 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2018. P. 974—978.</mixed-citation><mixed-citation xml:lang="en">Romanov A. M., Mikheenko I. S. A novel approach for creating modular reconfigurable robots with distributed power system, 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), IEEE, 2018, pp. 974—978.</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A., Slepynina E. Real-time Ethernet POWERLINK Communication for ROS. Part I. General Concept // 2020 Ural Smart Energy Conference (USEC). IEEE, 2020. P. 159—162.</mixed-citation><mixed-citation xml:lang="en">Romanov A., Slepynina E. Real-time Ethernet POWERLINK Communication for ROS. Part I. General Concept, 2020 Ural Smart Energy Conference (USEC). IEEE, 2020, pp. 159—162.</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A., Slepynina E. Real-time Ethernet POWERLINK Communication for ROS. Part II. Hardware and Software // 2020 Ural Smart Energy Conference (USEC). IEEE, 2020. P. 163—166.</mixed-citation><mixed-citation xml:lang="en">Romanov A., Slepynina E. Real-time Ethernet POWERLINK Communication for ROS. Part II. Hardware and Software, 2020 Ural Smart Energy Conference (USEC), IEEE, 2020, pp. 163—166.</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A. M., Gringoli F., Sikora A. A precise synchronization method for future wireless TSN networks // IEEE Transactions on Industrial Informatics. 2021. Vol. 17, N. 5. P. 3682—3692.</mixed-citation><mixed-citation xml:lang="en">Romanov A. M., Gringoli F., Sikora A. A precise synchronization method for future wireless TSN networks, IEEE Transactions on Industrial Informatics, 2021, vol. 17, no. 5, pp. 3682—3692.</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Romanov A. M. et al. Modular Reconfigurable Robot Distributed Computing System for Tracking Multiple Objects // IEEE Systems Journal. 2021. Vol. 15, N. 1. P. 802—813.</mixed-citation><mixed-citation xml:lang="en">Romanov A. M. et al. Modular Reconfigurable Robot Distributed Computing System for Tracking Multiple Objects, IEEE Systems Journal, 2021, vol. 15, no. 1, pp. 802—813.</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Rossi R. J. Mathematical statistics: an introduction to likelihood based inference. John Wiley &amp; Sons, 2018.</mixed-citation><mixed-citation xml:lang="en">Rossi R. J. Mathematical statistics: an introduction to likelihood based inference, John Wiley &amp; Sons, 2018.</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Hu Z. et al. Extrinsic calibration of 2-D laser rangefinder and camera from single shot based on minimal solution // IEEE Transactions on Instrumentation and Measurement. 2016. Vol. 65, N. 4. P. 915—929.</mixed-citation><mixed-citation xml:lang="en">Hu Z. et al. Extrinsic calibration of 2-D laser rangefinder and camera from single shot based on minimal solution, IEEE Transactions on Instrumentation and Measurement, 2016, vol. 65, no. 4, pp. 915—929.</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">Yang C., Duraiswami R., Davis L. Fast multiple object tracking via a hierarchical particle filter // Tenth IEEE International Conference on Computer Vision (ICCV’05). IEEE, 2005. Vol. 1. P. 212—219.</mixed-citation><mixed-citation xml:lang="en">Yang C., Duraiswami R., Davis L. Fast multiple object tracking via a hierarchical particle filter, Tenth IEEE International Conference on Computer Vision (ICCV’05), IEEE, 2005, vol. 1, pp. 212—219.</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Kong L. et al. Online Multiple Athlete Tracking with Pose-Based Long-Term Temporal Dependencies // Sensors. 2021. Vol. 21, N. 1. P. 197.</mixed-citation><mixed-citation xml:lang="en">Kong L. et al. Online Multiple Athlete Tracking with Pose-Based Long-Term Temporal Dependencies, Sensors, 2021, vol. 21, no. 1, pp. 197.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
