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    Information processing apparatus and method, and program for teaching an action to a device in a time-series pattern
    2.
    发明授权
    Information processing apparatus and method, and program for teaching an action to a device in a time-series pattern 失效
    信息处理装置和方法，以及用于以时间序列模式向装置教导动作的程序

    公开(公告)号：US07814037B2

    公开(公告)日：2010-10-12

    申请号：US11397148

    申请日：2006-04-04

    Applicant: Masato Ito ,  Yukiko Yoshiike ,  Kuniaki Noda ,  Jun Tani

    Inventor： Masato Ito ,  Yukiko Yoshiike ,  Kuniaki Noda ,  Jun Tani

    IPC: G05B13/02

    CPC classification number: B25J9/161 ,  G05B2219/36442 ,  G05B2219/40391 ,  G06N3/008

    Abstract: An information processing apparatus including a learning unit that learns a predetermined time-series pattern. An output unit outputs a time-series pattern corresponding to the result of learning by the learning unit. An adjusting unit supplied with a time-series pattern obtained from an action by an action unit on the basis of a time-series pattern supplied from the output unit and external teaching for the action adjusts a time-series pattern supplied from the output unit correspondingly to the input time-series pattern. The learning unit learns the time-series pattern supplied from the output unit and adjusted by the adjusting unit.

    Abstract translation: 一种信息处理设备，包括学习单元，该学习单元学习预定的时间序列模式。 输出单元输出与学习单元的学习结果相对应的时间序列模式。 相应地，从由输出单元提供的时间序列模式和由动作的外部教导基于由动作单元的动作获得的时间序列模式的调整单元相应地调整从输出单元提供的时间序列模式 到输入时间序列模式。 学习单元学习从输出单元提供并由调整单元调整的时间序列模式。

    Programming of a robotic arm using a motion capture system
    3.
    发明授权
    Programming of a robotic arm using a motion capture system 有权

    公开(公告)号：US09925669B2

    公开(公告)日：2018-03-27

    申请号：US15242875

    申请日：2016-08-22

    Applicant: X Development LLC

    Inventor： Jeffrey Linnell

    IPC: G06F19/00 ,  B25J9/16 ,  G05B19/427

    CPC classification number: B25J9/1697 ,  B25J9/1664 ,  G05B19/427 ,  G05B2219/36442 ,  G05B2219/37563 ,  Y10S901/01 ,  Y10S901/46 ,  Y10S901/47

    Abstract: An example method includes receiving position data indicative of position of a demonstration tool. Based on the received position data, the method further includes determining a motion path of the demonstration tool, wherein the motion path comprises a sequence of positions of the demonstration tool. The method additionally includes determining a replication control path for a robotic device, where the replication control path includes one or more robot movements that cause the robotic device to move a robot tool through a motion path that corresponds to the motion path of the demonstration tool. The method also includes providing for display of a visual simulation of the one or more robot movements within the replication control path.

    Rapid robotic imitation learning of force-torque tasks
    4.
    发明授权
    Rapid robotic imitation learning of force-torque tasks 有权
    快速机器人模拟学习力 - 扭矩任务

    公开(公告)号：US09403273B2

    公开(公告)日：2016-08-02

    申请号：US14285867

    申请日：2014-05-23

    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

    Inventor： David W. Payton ,  Ryan M. Uhlenbrock ,  Li Yang Ku

    IPC: B25J9/16 ,  G05B19/423

    CPC classification number: B25J9/163 ,  B25J9/1664 ,  G05B19/423 ,  G05B2219/36442 ,  Y10S901/03

    Abstract: A method of training a robot to autonomously execute a robotic task includes moving an end effector through multiple states of a predetermined robotic task to demonstrate the task to the robot in a set of n training demonstrations. The method includes measuring training data, including at least the linear force and the torque via a force-torque sensor while moving the end effector through the multiple states. Key features are extracted from the training data, which is segmented into a time sequence of control primitives. Transitions between adjacent segments of the time sequence are identified. During autonomous execution of the same task, a controller detects the transitions and automatically switches between control modes. A robotic system includes a robot, force-torque sensor, and a controller programmed to execute the method.

    Abstract translation: 训练机器人以自主执行机器人任务的方法包括：通过预定机器人任务的多个状态移动末端执行器，以在一组训练演示中向机器人演示任务。 该方法包括在通过多个状态移动末端执行器时通过力 - 转矩传感器测量训练数据至少包括线性力和扭矩。 从训练数据中提取主要特征，将其分为控制原语的时间序列。 识别时间序列的相邻片段之间的转换。 在相同任务的自主执行期间，控制器检测转换并在控制模式之间自动切换。 机器人系统包括机器人，力 - 扭矩传感器和被编程为执行该方法的控制器。

    NUMERICAL CONTROLLER
    5.
    发明申请
    NUMERICAL CONTROLLER 审中-公开
    数控系统

    公开(公告)号：US20160179083A1

    公开(公告)日：2016-06-23

    申请号：US14972774

    申请日：2015-12-17

    Applicant: FANUC Corporation

    Inventor： Takehiro YAMAGUCHI

    IPC: G05B19/408

    CPC classification number: G05B19/4083 ,  G05B19/425 ,  G05B2219/36442 ,  G05B2219/42129 ,  Y02P90/265

    Abstract: A numerical controller including an automatic display unit of a teach program includes a manual movement axis monitor unit for monitoring whether there is an axis moved by manual feed, a teach target program selection and determination unit for selecting and determining a teach program controlling the axis, and a teach block selection and determination unit for selecting and determining a teach point from a movement direction of the axis, and selecting and determining, as a teach block, a block in the teach program in which the teach point is an end point.

    Abstract translation: 包括教学程序的自动显示单元的数字控制器包括用于监视是否存在通过手动进给运动的轴的手动运动轴监视单元，用于选择和确定控制轴的教程序的教学目标程序选择和确定单元， 以及用于从所述轴的移动方向选择和确定教导点的教学块选择和确定单元，以及作为教学块的教学程序中选择并确定教学点为终点的程序块。

    Robot with automatic selection of task-specific representations for imitation learning
    6.
    发明授权
    Robot with automatic selection of task-specific representations for imitation learning 有权
    机器人自动选择任务特定的表示形式，用于模仿学习

    公开(公告)号：US08571714B2

    公开(公告)日：2013-10-29

    申请号：US12709814

    申请日：2010-02-22

    Applicant: Michael Gienger ,  Manuel Muehlig ,  Jochen Steil

    Inventor： Michael Gienger ,  Manuel Muehlig ,  Jochen Steil

    IPC: B25J13/08 ,  B25J19/04

    CPC classification number: G05B19/42 ,  G05B2219/36442

    Abstract: The invention proposes a method for imitation-learning of movements of a robot, wherein the robot performs the following steps: observing a movement of an entity in the robot's environment, recording the observed movement using a sensorial data stream and representing the recorded movement in a different task space representations, selecting a subset of the task space representations for the imitation learning and reproduction of the movement to be imitated.

    Abstract translation: 本发明提出了一种用于模仿学习机器人的运动的方法，其中机器人执行以下步骤：观察机器人环境中的实体的移动，使用感官数据流记录观察到的移动并将记录的运动表示在 不同的任务空间表示，选择任务空间表示的子集，用于仿制运动的仿制学习和再现。

    MACHINE LEARNING DEVICE FOR LEARNING ASSEMBLY OPERATION AND COMPONENT ASSEMBLY SYSTEM
    10.
    发明申请
    MACHINE LEARNING DEVICE FOR LEARNING ASSEMBLY OPERATION AND COMPONENT ASSEMBLY SYSTEM 审中-公开

    公开(公告)号：US20180180085A1

    公开(公告)日：2018-06-28

    申请号：US15835651

    申请日：2017-12-08

    Applicant: FANUC CORPORATION

    Inventor： Masato WATANABE ,  Taku SASAKI ,  Kiichi INABA

    IPC: F16B33/06 ,  G05B19/418

    CPC classification number: F16B33/06 ,  F16B5/02 ,  G05B19/41805 ,  G05B2219/36442 ,  G05B2219/40111 ,  G05B2219/45203 ,  Y02P90/02

    Abstract: A machine learning device includes a state observation unit for observing state variables that include at least one of the state of an assembly constituted of first and second components, an assembly time and information on a force, the result of a continuity test on the assembly, and at least one of position and posture command values for at least one of the first and second components and direction, speed and force command values for an assembly operation; and a learning unit for learning, in a related manner, at least one of the state of the assembly, the assembly time and the information on the force, the result of the continuity test on the assembly, and at least one of the position and posture command values for at least one of the first and second components and the direction, speed and force command values for the assembly operation.

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