The invention relates to a ship unloader intelligent operation method, device and equipment based on deep learning and a medium, and the method comprises the steps that grab bucket pose data collected by airborne detection equipment is acquired in real time, and the airborne detection equipment comprises a 3D laser radar; based on a trained deep learning model, obtaining an optimal grabbing curve corresponding to the grab bucket pose data and a movement control signal corresponding to the optimal grabbing curve; and based on the movement control signal, the ship unloader is controlled to conduct grabbing operation. The method has the effect that the optimal grabbing curve and the movement control signal can be quickly and effectively selected through the deep learning model by using the grab bucket pose data returned by the airborne detection equipment.

    本申请涉及基于深度学习的卸船机智能作业方法、装置、设备及介质,其方法包括:实时获取机载检测设备采集的抓斗位姿数据,所述机载检测设备包括3D激光雷达;基于训练好的深度学习模型,获取所述抓斗位姿数据对应的最优抓料曲线和所述最优抓料曲线对应的移动控制信号;基于所述移动控制信号,控制所述卸船机进行抓取作业。本申请具有利用机载检测设备传回的抓斗位姿数据,通过深度学习模型能够快速有效地选取出最优抓料曲线与移动控制信号的效果。


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    Title :

    Ship unloader intelligent operation method, device and equipment based on deep learning and medium


    Additional title:

    基于深度学习的卸船机智能作业方法、装置、设备及介质


    Contributors:
    DING JIAN (author) / CHI YIHENG (author) / LI JIANZHEN (author) / FANG GUOHAO (author) / GUO JIALIANG (author) / WANG HAOYU (author) / YANG WEIJIA (author) / HE DEMING (author) / ZHANG CHAOYANG (author) / KAN SHIYU (author)

    Publication date :

    2025-02-11


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    B66C Krane , CRANES



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