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System and method for real-time supervised machine learning in on-site environment

机译:现场环境中实时监控机器学习的系统和方法

摘要

An automatic guided vehicle (AGV) comprising a mobile base including a drive train and configured to drive the AGV in a self-navigation mode within a facility, a first camera configured to capture first image data of objects within the facility, a second camera configured to capture second image data of objects within the facility, the second camera including a content filter, and a main control module configured to receive the first and second image data from the first and second cameras. The main control module executes a recognition neural network program. The neural network program recognizes targets in the first image data. The main control module also executes a supervisor program under user control. The supervisor program is receives the second image data and recognizes markers attached to targets in the second image data. The supervisor program produces a supervised outcome in which targets to which markers are attached are associated with categories based on user commands. The supervised outcome adjusts weights of nodes in the recognition neural program.
机译:自动导向车辆(AGV)包括包括传动系的移动基站,并且被配置为在设施内的自动导航模式下驱动AGV,第一相机被配置为捕获设施内的对象的第一图像数据,配置了第二相机为了捕获设施内的对象的第二图像数据,包括内容滤波器的第二相机,以及被配置为从第一和第二相机接收第一和第二图像数据的主控制模块。主控制模块执行识别神经网络程序。神经网络程序识别第一图像数据中的目标。主控制模块还在用户控件下执行主管程序。主管程序是接收第二图像数据,并识别附加到第二图像数据中的目标的标记。主管程序产生了监督结果,其中附加标记的目标与基于用户命令的类别相关联。监督结果调整识别神经节目中节点的权重。

著录项

  • 公开/公告号US11092968B2

    专利类型

  • 公开/公告日2021-08-17

    原文格式PDF

  • 申请/专利权人 LINGDONG TECHNOLOGY (BEIJING) CO. LTD;

    申请/专利号US201816305007

  • 发明设计人 CHIUNG LIN CHEN;MENG YAO;

    申请日2018-11-15

  • 分类号G06K9/62;G05D1/02;G05D1;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-24 20:37:38

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