Design and implementation of intelligent tracking car based on machine vision
The intelligent tracking car can realize self-perception, behavioral decision-making, automatic driving, etc. for environmental information, and has a wide application in our lives. In this paper, a new intelligent car is designed based on STM32F407ZGT6 MCU. The track information is collected by the...
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Published in | Journal of intelligent & fuzzy systems Vol. 38; no. 5; pp. 5799 - 5810 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
IOS Press BV
01.01.2020
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Subjects | |
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Abstract | The intelligent tracking car can realize self-perception, behavioral decision-making, automatic driving, etc. for environmental information, and has a wide application in our lives. In this paper, a new intelligent car is designed based on STM32F407ZGT6 MCU. The track information is collected by the OV7725 camera. The fast OTSU adaptive threshold algorithm is used to obtain the path guiding center line, which can realize image collection, image analysis and sensor data fusion, blocked path identification and intelligent judgment, automatic tracking function. The test results show that the algorithm is effective and feasible. When there are obstacles or partial loss on the track, it can intelligently identify the effective and obstacles and realize the independent decision making. It has good dynamic and robustness. |
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AbstractList | The intelligent tracking car can realize self-perception, behavioral decision-making, automatic driving, etc. for environmental information, and has a wide application in our lives. In this paper, a new intelligent car is designed based on STM32F407ZGT6 MCU. The track information is collected by the OV7725 camera. The fast OTSU adaptive threshold algorithm is used to obtain the path guiding center line, which can realize image collection, image analysis and sensor data fusion, blocked path identification and intelligent judgment, automatic tracking function. The test results show that the algorithm is effective and feasible. When there are obstacles or partial loss on the track, it can intelligently identify the effective and obstacles and realize the independent decision making. It has good dynamic and robustness. |
Author | Lisang, Liu Junfeng, Fan Jing, Huang Jishi, Zheng Ying, Ma Jinxin, Yao Dongwei, He Xiaoyu, Wei |
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Cites_doi | 10.1109/IITA.2009.486 10.1080/02533839.2018.1537807 10.1109/ACCESS.2019.2891105 10.1007/s12652-018-1029-3 10.3233/JIFS-179491 10.1007/978-3-642-25185-6_69 10.1007/s12652-018-1144-1 10.3390/pr7110845 10.1177/1550147718764639 10.3233/JCM-180866 10.1109/TVLSI.2019.2903289 10.3233/JIFS-169874 10.1145/3363571 |
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Editor | Balas, Valentina Emilia Jain, Lakhmi C. |
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SubjectTerms | Adaptive algorithms Barriers Data integration Decision making Image analysis Machine vision Multisensor fusion Tracking |
Title | Design and implementation of intelligent tracking car based on machine vision |
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