In the autonomous motion control of unmanned equipment, in order to make the control more precise and efficient, in addition to the automatic operation of drones and unmanned vehicles, it is also necessary to introduce a certain amount of human-computer interaction. Therefore, in the control of unmanned equipment, it is very important to design a human-computer interaction program. In this paper, by analyzing the control requirements of unmanned equipment in specific cases and comparing with existing technologies, a gesture recognition program is established. The results show that it is feasible to control the movement of unmanned equipment through gesture recognition technology. Moreover, gesture control has the advantages of high accuracy, simplicity and efficiency, and can control multiple unmanned equipment in real time.


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    Titel :

    Autonomous Vehicles Based on Gesture Recognition Control Using CNN and CPM Model


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Long, Shengzhao (Herausgeber:in) / Dhillon, Balbir S. (Herausgeber:in) / Zhang, Xiulin (Autor:in) / Zhen, Chong (Autor:in) / Lei, Quxiao (Autor:in) / Wang, Yifeng (Autor:in) / Chen, Jiaao (Autor:in) / Jin, Weiyi (Autor:in) / Li, Ke (Autor:in) / Wang, Lijing (Autor:in)

    Kongress:

    International Conference on Man-Machine-Environment System Engineering ; 2022 ; Beijing, China October 21, 2022 - October 23, 2022



    Erscheinungsdatum :

    2022-08-21


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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