In order to enable mobile robots to work instead of human beings in places that human beings cannot normally explore, such as narrow pipes, collapsed ruins, high-risk areas after earthquake or fire, an environmental identification experimental system is designed and built. This system combines the recognition and application principle of binocular stereo vision to build a vision system, so that the robot has similar to human eyes; Then equipped with radar to assist, so that the robot has human hearing at the same time, so that the robot can imitate human to achieve effective acceptance and recognition of environmental information. Finally, the recognition system is tested in different scenarios. The results show that the recognition system not only achieves the expected goal, but also has high portability due to the step-by-step construction.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Smart Mobile Robot's Binocular Stereo Vision Environment Recognition Experimental System Design at Slow Speed


    Beteiligte:
    Qian, Suke (Autor:in) / Yang, Jie (Autor:in)


    Erscheinungsdatum :

    2022-12-01


    Format / Umfang :

    454553 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Binocular stereo vision system design for lunar rover

    Chu, J. / Jiao, C. / Guo, H. et al. | British Library Conference Proceedings | 2007


    Vehicle speed intelligent measurement method based on binocular stereo vision system

    YANG LEI / SONG XIAOWEI / LI MENGLONG et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    VEHICLE SPEED INTELLIGENT MEASUREMENT METHOD BASED ON BINOCULAR STEREO VISION SYSTEM

    YANG LEI / SONG XIAOWEI / LI MENGLONG et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Binocular stereo vision technology based on human visual characteristics

    Zhao, Jing / Sui, Xiubao / Zhu, Haoyao et al. | SPIE | 2021