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。

公开(公告)号：US20150094852A1

公开(公告)日：2015-04-02

申请号：US14040498

申请日：2013-09-27

Applicant: BRAIN CORPORATION

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

IPC: B25J9/16

CPC classification number: B25J9/163 ,  G05B2219/40494 ,  G05D1/00 ,  G05D1/0246 ,  G06N3/008 ,  G06N3/049 ,  Y10S901/03 ,  Y10S901/09

Abstract: Apparatus and methods for arbitration of control signals for robotic devices. A robotic device may comprise an adaptive controller comprising a plurality of predictors configured to provide multiple predicted control signals based on one or more of the teaching input, sensory input, and/or performance. The predicted control signals may be configured to cause two or more actions that may be in conflict with one another and/or utilize a shared resource. An arbitrator may be employed to select one of the actions. The selection process may utilize a WTA, reinforcement, and/or supervisory mechanisms in order to inhibit one or more predicted signals. The arbitrator output may comprise target state information that may be provided to the predictor block. Prior to arbitration, the predicted control signals may be combined with inputs provided by an external control entity in order to reduce learning time.

Abstract translation: 用于对机器人装置的控制信号进行仲裁的装置和方法。 机器人设备可以包括自适应控制器，其包括多个预测器，其被配置为基于教学输入，感觉输入和/或性能中的一个或多个来提供多个预测控制信号。 预测的控制信号可以被配置为引起可能彼此冲突和/或利用共享资源的两个或更多个动作。 仲裁员可以用来选择一个动作。 选择过程可以利用WTA，加强和/或监督机制来抑制一个或多个预测信号。 仲裁器输出可以包括可以提供给预测器块的目标状态信息。 在仲裁之前，预测的控制信号可以与由外部控制实体提供的输入组合以减少学习时间。

公开(公告)号：US10818016B2

公开(公告)日：2020-10-27

申请号：US16357536

申请日：2019-03-19

Applicant: BRAIN CORPORATION

Inventor： Filip Piekniewski ,  Micah Richert ,  Dimitry Fisher ,  Patryk Laurent ,  Csaba Petre

IPC: G06T7/20 ,  G06T1/60 ,  G06T9/00 ,  G06T7/00 ,  H04N19/503 ,  G06F12/08

Abstract: Systems and methods for predictive/reconstructive visual object tracking are disclosed. The visual object tracking has advanced abilities to track objects in scenes, which can have a variety of applications as discussed in this disclosure. In some exemplary implementations, a visual system can comprise a plurality of associative memory units, wherein each associative memory unit has a plurality of layers. The associative memory units can be communicatively coupled to each other in a hierarchical structure, wherein data in associative memory units in higher levels of the hierarchical structure are more abstract than lower associative memory units. The associative memory units can communicate to one another supplying contextual data.

公开(公告)号：US20190321973A1

公开(公告)日：2019-10-24

申请号：US16402758

申请日：2019-05-03

Applicant: Brain Corporation

Inventor： Philip Meier ,  Jean-Baptiste Passot ,  Borja Ibarz Gabardos ,  Patryk Laurent ,  Oleg Sinyavskiy ,  Peter O'Connor ,  Eugene Izhikevich

IPC: B25J9/16 ,  G06N20/00 ,  G06N3/00 ,  G05D1/00 ,  G05B13/02

Abstract: Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

公开(公告)号：US20190302714A1

公开(公告)日：2019-10-03

申请号：US16376206

申请日：2019-04-05

Applicant: BRAIN CORPORATION

Inventor： Patryk Laurent ,  Eugene Izhikevich

IPC: G05B15/02 ,  H04L12/28 ,  H04M1/725 ,  G06F3/03 ,  H04W4/021 ,  G06F3/038 ,  G06F3/01

Abstract: Gesture recognition systems that are configured to provide users with simplified operation of various controllable devices such as, for example, in-home controllable devices. In one implementation, the gesture recognition system automatically configures itself in order to determine the respective physical locations and/or identities of controllable devices as well as an operating mode for controlling the controllable devices through predetermined gesturing. In some implementations, the gesture recognition systems are also configured to assign boundary areas associated with the controllable devices. Apparatus and methods associated with the gesture recognition systems are also disclosed.

公开(公告)号：US10369694B2

公开(公告)日：2019-08-06

申请号：US15960300

申请日：2018-04-23

Applicant: Brain Corporation

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

IPC: G05B19/18 ,  B25J9/16 ,  G06N3/00 ,  G06N3/04

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.

公开(公告)号：US20180018775A1

公开(公告)日：2018-01-18

申请号：US15627096

申请日：2017-06-19

Applicant: Brain Corporation

Inventor： Filip Piekniewski ,  Micah Richert ,  Dimitry Fisher ,  Patryk Laurent ,  Csaba Petre

IPC: G06T7/20 ,  G06T7/00 ,  G06T1/60 ,  G06T9/00 ,  G06F12/08

CPC classification number: G06T7/20 ,  G06F12/08 ,  G06F2212/1016 ,  G06F2212/401 ,  G06T1/60 ,  G06T7/0002 ,  G06T9/002 ,  G06T9/004 ,  G06T2207/20084

Abstract: Systems and methods for predictive/reconstructive visual object tracking are disclosed. The visual object tracking has advanced abilities to track objects in scenes, which can have a variety of applications as discussed in this disclosure. In some exemplary implementations, a visual system can comprise a plurality of associative memory units, wherein each associative memory unit has a plurality of layers. The associative memory units can be communicatively coupled to each other in a hierarchical structure, wherein data in associative memory units in higher levels of the hierarchical structure are more abstract than lower associative memory units. The associative memory units can communicate to one another supplying contextual data.

公开(公告)号：US09860077B2

公开(公告)日：2018-01-02

申请号：US14489353

申请日：2014-09-17

Applicant: Brain Corporation

Inventor： Patryk Laurent ,  Csaba Petre ,  Eugene M. Izhikevich

IPC: G05B15/00 ,  G05B19/00 ,  H04L12/28 ,  G05B15/02

CPC classification number: H04L12/282 ,  G05B15/02 ,  G05B2219/2642 ,  G05B2219/40411 ,  H01H2300/03 ,  Y02B70/325 ,  Y04S20/228

Abstract: Computerized appliances may be operated by users remotely. A learning controller apparatus may be operated to determine association between a user indication and an action by the appliance. The user indications, e.g., gestures, posture changes, audio signals may trigger an event associated with the controller. The event may be linked to a plurality of instructions configured to communicate a command to the appliance. The learning apparatus may receive sensory input conveying information about robot's state and environment (context). The sensory input may be used to determine the user indications. During operation, upon determine the indication using sensory input, the controller may cause execution of the respective instructions in order to trigger action by the appliance. Device animation methodology may enable users to operate computerized appliances using gestures, voice commands, posture changes, and/or other customized control elements.

公开(公告)号：US09579790B2

公开(公告)日：2017-02-28

申请号：US14489373

申请日：2014-09-17

Applicant: Brain Corporation

Inventor： Patryk Laurent ,  Csaba Petre ,  Eugene M. Izhikevich ,  Vadim Polonichko

IPC: B25J9/16

CPC classification number: B25J9/163 ,  G05B2219/2642 ,  G05B2219/40116 ,  Y10S901/05

Abstract: Computerized appliances may be operated by users remotely. In one implementation, a learning controller apparatus may be operated to determine association between a user indication and an action by the appliance. The user indications, e.g., gestures, posture changes, audio signals may trigger an event associated with the controller. The event may be linked to a plurality of instructions configured to communicate a command to the appliance. The learning apparatus may receive sensory input conveying information about robot's state and environment (context). The sensory input may be used to determine the user indications. During operation, upon determine the indication using sensory input, the controller may cause execution of the respective instructions in order to trigger action by the appliance. Device animation methodology may enable users to operate computerized appliances using gestures, voice commands, posture changes, and/or other customized control elements.

Abstract translation: 计算机化设备可由用户远程操作。 在一个实现中，可以操作学习控制器设备以确定用户指示与设备的动作之间的关联。 用户指示，例如手势，姿势改变，音频信号可以触发与控制器相关联的事件。 事件可以被链接到被配置为向设备传达命令的多个指令。 学习装置可以接收关于机器人的状态和环境（上下文）的感官输入。 感官输入可用于确定用户指示。 在操作期间，在使用感觉输入确定指示时，控制器可以引起相应指令的执行，以触发设备的动作。 设备动画方法可以使用户能够使用手势，语音命令，姿势改变和/或其他定制的控制元素来操作计算机化的设备。

公开(公告)号：US09384443B2

公开(公告)日：2016-07-05

申请号：US13918338

申请日：2013-06-14

Applicant: BRAIN CORPORATION

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

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

CPC classification number: B25J9/163 ,  B25J9/161 ,  G05D1/0221 ,  G06N3/008 ,  G06N3/049 ,  G06N3/08

Abstract: Apparatus and methods for training of robotic devices. Robotic devices may be trained by a user guiding the robot along target trajectory using an input signal. A robotic device may comprise an adaptive controller configured to generate control commands based on one or more of the user guidance, sensory input, and/or performance measure. Training may comprise a plurality of trials. During first trial, the user input may be sufficient to cause the robot to complete the trajectory. During subsequent trials, the user and the robot's controller may collaborate so that user input may be reduced while the robot control may be increased. Individual contributions from the user and the robot controller during training may be may be inadequate (when used exclusively) to complete the task. Upon learning, user's knowledge may be transferred to the robot's controller to enable task execution in absence of subsequent inputs from the user.

Abstract translation: 用于训练机器人装置的装置和方法。 机器人装置可以由用户使用输入信号沿目标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，感觉输入和/或性能测量中的一个或多个来产生控制命令。 培训可能包括多项试验。 在第一次试用期间，用户输入可能足以使机器人完成轨迹。 在随后的试验期间，用户和机器人的控制器可以协作，以便可以减少用户输入，同时可以增加机器人控制。 在训练期间来自用户和机器人控制器的个人贡献可能不足以（完全用于完成任务）。 在学习之后，用户的知识可以传送到机器人的控制器，以便在没有用户的后续输入的情况下执行任务执行。