中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

25 records (took 0.02 seconds)

    Predictive robotic controller apparatus and methods
    11.
    发明授权
    Predictive robotic controller apparatus and methods 有权
    预测机器人控制器设备及方法

    公开(公告)号：US09314924B1

    公开(公告)日：2016-04-19

    申请号：US13918620

    申请日：2013-06-14

    Applicant: BRAIN CORPORATION

    Inventor： Patryk Laurent ,  Jean-Baptiste Passot ,  Oleg Sinyavskiy ,  Filip Ponulak ,  Borja Ibarz Gabardos ,  Eugene Izhikevich

    IPC: G05B19/18 ,  B25J9/16

    CPC classification number: B25J9/163 ,  G05B2219/39271 ,  G05B2219/39289 ,  G06N3/008 ,  G06N3/049

    Abstract: Robotic devices may be trained by a user guiding the robot along target action trajectory using an input signal. A robotic device may comprise an adaptive controller configured to generate control signal based on one or more of the user guidance, sensory input, performance measure, and/or other information. Training may comprise a plurality of trials, wherein for a given context the user and the robot's controller may collaborate to develop an association between the context and the target action. Upon developing the association, the adaptive controller may be capable of generating the control signal and/or an action indication prior and/or in lieu of user input. The predictive control functionality attained by the controller may enable autonomous operation of robotic devices obviating a need for continuing user guidance.

    Abstract translation: 机器人设备可以由用户使用输入信号沿着目标动作轨迹引导机器人进行训练。 机器人设备可以包括自适应控制器，其被配置为基于用户引导，感觉输入，性能测量和/或其他信息中的一个或多个来产生控制信号。 培训可以包括多个试验，其中对于给定的上下文，用户和机器人的控制器可以协作以在上下文和目标动作之间建立关联。 在开发关联时，自适应控制器可以能够在用户输入之前和/或代替用户输入时产生控制信号和/或动作指示。 由控制器获得的预测控制功能可以实现机器人设备的自主操作，从而避免需要持续的用户指导。

    Apparatus and methods for gating analog and spiking signals in artificial neural networks
    12.
    发明授权
    Apparatus and methods for gating analog and spiking signals in artificial neural networks 有权
    在人造神经网络中门控模拟和加标信号的装置和方法

    公开(公告)号：US09213937B2

    公开(公告)日：2015-12-15

    申请号：US13761090

    申请日：2013-02-06

    Applicant: Brain Corporation

    Inventor： Filip Ponulak

    IPC: G06F15/18 ,  G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/049

    Abstract: Apparatus and methods for universal node design implementing a universal learning rule in a mixed signal spiking neural network. In one implementation, at one instance, the node apparatus, operable according to the parameterized universal learning model, receives a mixture of analog and spiking inputs, and generates a spiking output based on the model parameter for that node that is selected by the parameterized model for that specific mix of inputs. At another instance, the same node receives a different mix of inputs, that also may comprise only analog or only spiking inputs and generates an analog output based on a different value of the node parameter that is selected by the model for the second mix of inputs. In another implementation, the node apparatus may change its output from analog to spiking responsive to a training input for the same inputs.

    Abstract translation: 通用节点设计的装置和方法在混合信号加标神经网络中实现通用学习规则。 在一个实现中，在一个实例中，节点装置可根据参数化通用学习模型操作，接收模拟和加注输入的混合，并且基于由参数化模型选择的该节点的模型参数生成加标输出 对于具体的投入组合。 在另一个实例中，同一节点接收不同的输入混合，其也可以仅包括模拟或仅包括输入，并且基于由模型为第二混合输入选择的节点参数的不同值生成模拟输出 。 在另一实现中，节点装置可以响应于针对相同输入的训练输入而将其输出从模拟改变为尖峰。

    ACTION SELECTION APPARATUS AND METHODS
    13.
    发明申请
    ACTION SELECTION APPARATUS AND METHODS 审中-公开
    行动选择装置和方法

    公开(公告)号：US20150005937A1

    公开(公告)日：2015-01-01

    申请号：US13928775

    申请日：2013-06-27

    Applicant: BRAIN CORPORATION

    Inventor： Filip Ponulak

    IPC: B25J9/16 ,  G06N3/02

    CPC classification number: G06N3/049 ,  Y10S901/01 ,  Y10S901/47

    Abstract: An action for execution by a robotic device may be selected. A robotic controller may determine that two or more actions are to be executed based on analysis of sensory and/or training input. The actions may comprise target approach and/or obstacle avoidance. Execution of individual actions may be based on a control signal and a separate activation signal being generated by the controller. Control signal execution may be inhibited by the controller relay block. Multiple activation signals may compete with one another in winner-take-all action selection network to produce selection signal. The selection signal may temporarily pause inhibition of a respective portion of the relay block that is associated with the winning activation signal channel. A disinhibited portion of the relay block may provide the respective control signal for execution by a controllable element. Arbitration between individual actions may be performed based on evaluation of activation signals.

    Abstract translation: 可以选择由机器人装置执行的动作。 机器人控制器可以基于感官和/或训练输入的分析来确定要执行两个或多个动作。 动作可以包括目标方法和/或障碍物避免。 各个动作的执行可以基于由控制器产生的控制信号和单独的激活信号。 控制器继电器块可能会禁止控制信号的执行。 多个激活信号可以在获胜者全部动作选择网络中彼此竞争，以产生选择信号。 选择信号可以临时暂停与获胜激活信号信道相关联的中继块的相应部分的禁止。 继电器块的无限制部分可以提供用于由可控元件执行的相应控制信号。 可以基于激活信号的评估来执行各个动作之间的仲裁。

    HIERARCHICAL ROBOTIC CONTROLLER APPARATUS AND METHODS
    14.
    发明申请
    HIERARCHICAL ROBOTIC CONTROLLER APPARATUS AND METHODS 有权
    分层机器人控制器装置及方法

    公开(公告)号：US20140371912A1

    公开(公告)日：2014-12-18

    申请号：US13918298

    申请日：2013-06-14

    Applicant: BRAIN CORPORATION

    Inventor： Jean-Baptiste Passot ,  Oleg Sinyavskiy ,  Filip Ponulak ,  Patryk Laurent ,  Borja Ibarz Gabardos ,  Eugene Izhikevich ,  Vadim Polonichko

    IPC: B25J9/16

    CPC classification number: G06N3/049 ,  G06N3/008

    Abstract: A robot may be trained by a user guiding the robot along target trajectory using a control signal. A robot may comprise an adaptive controller. The controller may be configured to generate control commands based on the user guidance, sensory input and a performance measure. A user may interface to the robot via an adaptively configured remote controller. The remote controller may comprise a mobile device, configured by the user in accordance with phenotype and/or operational configuration of the robot. The remote controller may detect changes in the robot phenotype and/or operational configuration. The remote controller may comprise multiple control elements configured to activate respective portions of the robot platform. Based on training, the remote controller may configure composite controls configured based two or more of control elements. Activation of a composite control may enable the robot to perform a task.

    Abstract translation: 机器人可以由使用者使用控制信号沿目标轨迹引导机器人的用户进行训练。 机器人可以包括自适应控制器。 控制器可以被配置为基于用户指导，感觉输入和性能测量来产生控制命令。 用户可以通过自适应配置的遥控器与机器人接口。 遥控器可以包括由用户根据机器人的表型和/或操作配置来配置的移动设备。 遥控器可以检测机器人表型和/或操作配置的变化。 遥控器可以包括配置成激活机器人平台的相应部分的多个控制元件。 基于培训，遥控器可以配置基于两个或多个控制元件的复合控制。 激活复合控件可以使机器人执行任务。

    Apparatus and methods for haptic training of robots
    15.
    发明授权
    Apparatus and methods for haptic training of robots 有权

    公开(公告)号：US10717191B2

    公开(公告)日：2020-07-21

    申请号：US15845832

    申请日：2017-12-18

    Applicant: Brain Corporation

    Inventor： Filip Ponulak ,  Moslem Kazemi ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Eugene Izhikevich

    IPC: B25J9/00 ,  B25J9/16 ,  G05D1/00 ,  G05D1/02 ,  G06N20/00 ,  G06N3/00 ,  G06N3/04

    Abstract: Robotic devices may be trained by a trainer guiding the robot along a target trajectory using physical contact with the robot. The robot may comprise an adaptive controller configured to generate control commands based on one or more of the trainer input, sensory input, and/or performance measure. The trainer may observe task execution by the robot. Responsive to observing a discrepancy between the target behavior and the actual behavior, the trainer may provide a teaching input via a haptic action. The robot may execute the action based on a combination of the internal control signal produced by a learning process of the robot and the training input. The robot may infer the teaching input based on a comparison of a predicted state and actual state of the robot. The robot's learning process may be adjusted in accordance with the teaching input so as to reduce the discrepancy during a subsequent trial.

    APPARATUS AND METHODS FOR HAPTIC TRAINING OF ROBOTS
    17.
    发明申请
    APPARATUS AND METHODS FOR HAPTIC TRAINING OF ROBOTS 审中-公开

    公开(公告)号：US20180272529A1

    公开(公告)日：2018-09-27

    申请号：US15845832

    申请日：2017-12-18

    Applicant: Brain Corporation

    Inventor： Filip Ponulak ,  Moslem Kazemi ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Eugene Izhikevich

    IPC: B25J9/16 ,  G05D1/02 ,  G05D1/00

    Abstract: Robotic devices may be trained by a trainer guiding the robot along a target trajectory using physical contact with the robot. The robot may comprise an adaptive controller configured to generate control commands based on one or more of the trainer input, sensory input, and/or performance measure. The trainer may observe task execution by the robot. Responsive to observing a discrepancy between the target behavior and the actual behavior, the trainer may provide a teaching input via a haptic action. The robot may execute the action based on a combination of the internal control signal produced by a learning process of the robot and the training input. The robot may infer the teaching input based on a comparison of a predicted state and actual state of the robot. The robot's learning process may be adjusted in accordance with the teaching input so as to reduce the discrepancy during a subsequent trial.

    DISCREPANCY DETECTION APPARATUS AND METHODS FOR MACHINE LEARNING
    20.
    发明申请
    DISCREPANCY DETECTION APPARATUS AND METHODS FOR MACHINE LEARNING 有权
    差异检测装置和机器学习方法

    公开(公告)号：US20150148953A1

    公开(公告)日：2015-05-28

    申请号：US14088258

    申请日：2013-11-22

    Applicant: Brain Corporation

    Inventor： Patryk Laurent ,  Jean-Baptiste Passot ,  Filip Ponulak ,  Eugene Izhikevich

    IPC: B25J9/16

    CPC classification number: B25J9/163 ,  G05B13/026 ,  G05B2219/40512 ,  G05B2219/42058 ,  G05D1/0088 ,  G05D2201/02 ,  G06N3/049 ,  G06N99/005

    Abstract: A robotic device may comprise an adaptive controller configured to learn to predict consequences of robotic device's actions. During training, the controller may receive a copy of the planned and/or executed motor command and sensory information obtained based on the robot's response to the command. The controller may predict sensory outcome based on the command and one or more prior sensory inputs. The predicted sensory outcome may be compared to the actual outcome. Based on a determination that the prediction matches the actual outcome, the training may stop. Upon detecting a discrepancy between the prediction and the actual outcome, the controller may provide a continuation signal configured to indicate that additional training may be utilized. In some classification implementations, the discrepancy signal may be used to indicate occurrence of novel (not yet learned) objects in the sensory input and/or indicate continuation of training to recognize said objects.

    Abstract translation: 机器人设备可以包括被配置为学习预测机器人设备的动作的后果的自适应控制器。 在训练期间，控制器可以接收基于机器人对命令的响应获得的计划和/或执行的电动机命令和感觉信息的副本。 控制器可以基于命令和一个或多个现有的感觉输入来预测感觉结果。 预测的感觉结果可能与实际结果进行比较。 根据预测与实际结果的匹配，培训可能会停止。 在检测到预测和实际结果之间的差异时，控制器可以提供被配置为指示可以利用附加训练的连续信号。 在一些分类实现中，差异信号可以用于指示感觉输入中的新颖（尚未学习）的对象的发生和/或指示用于识别所述对象的训练的继续。

Patent Agency Ranking