Автономды көлiктер үшiн компьютерлiк көру модулiн әзiрлеу
DOI:
https://doi.org/10.26577/JMMCS.2022.v116.i4.06Кілттік сөздер:
Компьютерлiк көру, автономды көлiк, көлiк траекториясын жоспарлау, нақты уақыттағы траекторияны жоспарлау, адамсыз шешiмАннотация
Қазақстанның оңтайлы геосаяси жағдайы мен Қытай мен Еуропа арасындағы жүк тасымалы саласында Қазақстан Республикасының үлкен транзиттiк әлеуетi көлiктiк-логистикалық саланы ел экономикасын дамыту үшiн перспективалы бағыттардың бiрi болып табылады. Осы тұрғыда отын тұтыну шығындарын азайту және адам еңбегiн пайдаланудың логистикалық үдерiстердiң iшiнде, сондай-ақ қоғамдық көлiктердегi жүктердi тасымалдау кезiнде пайдаланбайтын жүктердiң технологиясын пайдалану табиғи және тиiмдi болып көрiнедi.
Бұл мақалада автономды жүк көлiгiнiң прототипi үшiн компьютерлiк көру модулiн әзiрлеу бойынша зерттеу жұмысының нәтижелерi сипатталған. Орындалған жоба кезеңдерi қажеттi жабдықты орнатуды, компьютерлiк көру үлгiлерiн дайындау және объектiлердi жiктеу және локализациялау мақсатында камералар мен LIDAR сенсоры арасындағы картаны әзiрлеудi қамтиды.
Библиографиялық сілтемелер
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[13] Abilkassov Sh., Nurlybayev A., Soltan S., Kim A., Shpieva E., Yesmagambet N., Yessenbayev Zh., Shintemirov A., “Facilitating Autonomous Vehicle Research and Development Using Robot Simulators on the Example of a KAMAZ NEO Truck” , 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), (2020):1-8.
[14] Zhang Zh, “A Flexible New Technique for Camera Calibration” , IEEE Trans. Pattern Anal. Mach. Intell., 22(11), (2000):1330-1334.
[15] Abdel-Aziz Y.I., Karara H.M., “Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry” , In Proceedings of the Symposium on Close-Range Photogrammetry, 8 (1971):1-18.
[16] “cvlib - a simple, high level, easy to use, open source Computer Vision library for Python” , accessed: 07.07.2022, URL: https://www.cvlib.net/.
[17] “ArUco: a minimal library for Augmented Reality applications based on OpenCV” , accessed: 07.07.2022, URL: https://www.uco.es/investiga/grupos/ava/node/26.
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[20] “Russian Traffic Sign Dataset” , accessed: 07.07.2022, URL: http://graphics.cs.msu.ru/en/research/projects/rtsd.
[21] Redmon J., Divvala S., Girshick R., Farhadi A., “You only look once: Unified, real-time object detection” , In Proceedings of the IEEE conference on computer vision and pattern recognition, (2016):779-788.
[22] Duan K., Bai S., Xie L., Qi H., Huang Q.,Tian Q., “CenterNet: Keypoint Triplets for Object Detection” , In Proceedings of the IEEE/CVF international conference on computer vision, (2019):6569-6578.
[23] Geiger A., Lenz P., Stiller C., Urtasun R., “Vision meets robotics: The KITTI dataset” , International Journal of Robotics Results, 32(11)(2013):1231–1237.
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Как цитировать
Yessenbayev, Z., Kozhirbayev, Z., & Shintemirov, A. (2022). Автономды көлiктер үшiн компьютерлiк көру модулiн әзiрлеу. Қазұу Хабаршысы. Математика, механика, информатика сериясы, 116(4). https://doi.org/10.26577/JMMCS.2022.v116.i4.06
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