This paper addresses the labor shortages and high costs in traditional agriculture by designing an intelligent orchard picking robot. The robot leverages the ROS operating system, NVIDIA Jetson Nano, and a tracked chassis to navigate complex terrains. Key technologies include SLAM for real-time mapping, A* for path planning, and YOLOv5 for fruit detection. Experiments conducted in a simulated orchard environment demonstrate the robot's effectiveness in autonomous navigation and accurate fruit recognition, achieving 95% recognition accuracy in clear conditions and 75% under occlusion. The results showcase the robot's potential to significantly enhance productivity and reduce labor demands in orchard harvesting.


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    Titel :

    Design and Implementation of Intelligent Orchard Robot


    Beteiligte:
    Wu, Jiaming (Autor:in) / Ge, Yuxuan (Autor:in) / Wu, Jianxiong (Autor:in) / Cao, Jin (Autor:in) / Feng, Junhao (Autor:in)


    Erscheinungsdatum :

    13.12.2024


    Format / Umfang :

    3579075 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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