首页> 外国专利> MACHINE LEARNING DEVICE AND MACHINE LEARNING METHOD FOR LEARNING OPTIMAL OBJECT GRASP ROUTE

MACHINE LEARNING DEVICE AND MACHINE LEARNING METHOD FOR LEARNING OPTIMAL OBJECT GRASP ROUTE

机译:学习最佳对象网格路径的机器学习设备和机器学习方法

摘要

A machine learning device according to the present invention learns an operation condition of a robot that stores a plurality of objects disposed on a carrier device in a container using a hand for grasping the objects. The machine learning device includes a state observation unit for observing the positions and postures of the objects and a state variable including at least one of cycle time to store the objects in the container and torque and vibration occurring when the robot grasps the objects during operation of the robot; a determination data obtaining unit for obtaining determination data for determining a margin of each of the cycle time, the torque, and the vibration against an allowance value; and a learning unit for learning the operation condition of the robot in accordance with a training data set constituted of a combination of the state variable and the determination data.
机译:根据本发明的机器学习装置使用用于抓握物体的手来学习将放置在承载装置上的多个物体存储在容器中的机器人的操作条件。该机器学习装置包括:状态观察单元,用于观察对象的位置和姿势;以及状态变量,其包括以下至少一项:将对象存储在容器中的循环时间;以及在机器人的操作过程中当机器人抓住对象时发生的扭矩和振动。机器人;确定数据获取单元,用于获取确定数据,该确定数据用于确定每个循环时间,转矩和振动相对于容差值的裕度;学习单元,用于根据由状态变量和确定数据的组合构成的训练数据集来学习机器人的操作状态。

著录项

  • 公开/公告号US2018089589A1

    专利类型

  • 公开/公告日2018-03-29

    原文格式PDF

  • 申请/专利权人 FANUC CORPORATION;

    申请/专利号US201715708130

  • 发明设计人 MASAFUMI OOBA;

    申请日2017-09-19

  • 分类号G06N99;B25J9/16;B25J13/08;

  • 国家 US

  • 入库时间 2022-08-21 13:01:28

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