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    LEARNING APPARATUS AND METHODS FOR CONTROL OF ROBOTIC DEVICES VIA SPOOFING
    1.
    发明申请
    LEARNING APPARATUS AND METHODS FOR CONTROL OF ROBOTIC DEVICES VIA SPOOFING 有权
    学习装置和方法通过交付控制机器人装置

    公开(公告)号：US20150283702A1

    公开(公告)日：2015-10-08

    申请号：US14244888

    申请日：2014-04-03

    Applicant: BRAIN CORPORATION

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

    IPC: B25J9/16

    CPC classification number: B25J9/163 ,  B25J9/161 ,  G05D1/0022 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/02 ,  G06N3/008 ,  G06N3/049 ,  G06N99/005

    Abstract: Robotic devices may be operated by users remotely. A learning controller apparatus may detect remote transmissions comprising user control instructions. The learning apparatus may receive sensory input conveying information about robot's state and environment (context). The learning apparatus may monitor one or more wavelength (infrared light, radio channel) and detect transmissions from user remote control device to the robot during its operation by the user. The learning apparatus may be configured to develop associations between the detected user remote control instructions and actions of the robot for given context. When a given sensory context occurs, the learning controller may automatically provide control instructions to the robot that may be associates with the given context. The provision of control instructions to the robot by the learning controller may obviate the need for user remote control of the robot thereby enabling autonomous operation by the robot.

    Abstract translation: 机器人设备可以由用户远程操作。 学习控制器装置可以检测包括用户控制指令的远程传输。 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。 学习装置可以监视一个或多个波长（红外光，无线电信道），并且在用户操作期间检测从用户遥控装置到机器人的传输。 学习装置可以被配置为在给定的上下文之间发展检测到的用户远程控制指令和机器人的动作之间的关联。 当发生给定的感觉上下文时，学习控制器可以自动向可能与给定上下文相关联的机器人提供控制指令。 通过学习控制器向机器人提供控制指令可以避免用户对机器人的远程控制的需要，从而实现机器人的自主操作。

    Systems and methods for predictive/reconstructive visual object tracker
    2.
    发明授权
    Systems and methods for predictive/reconstructive visual object tracker 有权

    公开(公告)号：US10282849B2

    公开(公告)日：2019-05-07

    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: G06T7/00 ,  G06T1/60 ,  G06T7/20 ,  G06T9/00 ,  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.

    Spiking neuron sensory processing apparatus and methods for saliency detection
    3.
    发明授权
    Spiking neuron sensory processing apparatus and methods for saliency detection 有权
    尖峰神经元感觉处理装置及显着检测方法

    公开(公告)号：US09218563B2

    公开(公告)日：2015-12-22

    申请号：US13660982

    申请日：2012-10-25

    Applicant: Brain Corporation

    Inventor： Botond Szatmary ,  Micah Richert ,  Eugene Izhikevich ,  Jayram Moorkanikara Nageswaran ,  Filip Piekniewski ,  Sach Sokol ,  Csaba Petre

    IPC: G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00 ,  G06N3/02 ,  G06F15/00 ,  G06F17/00 ,  G06N3/10

    CPC classification number: G06N3/02 ,  G06N3/049 ,  G06N3/063 ,  G06N3/088

    Abstract: Apparatus and methods for salient feature detection by a spiking neuron network. The network may comprise feature-specific units capable of responding to different objects (red and green color). The plasticity mechanism of the network may be configured based on difference between two similarity measures related to activity of different unit types obtained during network training. One similarity measure may be based on activity of units of the same type (red). Another similarity measure may be based on activity of units of one type (red) and another type (green). Similarity measures may comprise a cross-correlogram and/or mutual information determined over an activity window. During network operation, the activity based plasticity mechanism may be used to potentiate connections between units of the same type (red-red). The plasticity mechanism may be used to depress connections between units of different types (red-green). The plasticity mechanism may effectuate detection of salient features in the input.

    Abstract translation: 通过尖峰神经元网络显着特征检测的装置和方法。 网络可以包括能够响应于不同对象（红色和绿色）的特征单元。 网络的可塑性机制可以基于网络训练过程中获得的不同单元类型的活动相关的两个相似性度量之间的差异进行配置。 一个相似性度量可以基于相同类型（红色）的单元的活动。 另一种相似性度量可以基于一种类型（红色）和另一种类型（绿色）的单位的活动。 相似性度量可以包括在活动窗口上确定的交叉相关图和/或相互信息。 在网络运行期间，基于活动的可塑性机制可用于加强相同类型（红 - 红）单元之间的连接。 可塑性机制可用于抑制不同类型（红 - 绿）单元之间的连接。 可塑性机制可能会影响输入中突出特征的检测。

    Apparatus and methods for context determination using real time sensor data
    6.
    发明授权
    Apparatus and methods for context determination using real time sensor data 有权

    公开(公告)号：US09821470B2

    公开(公告)日：2017-11-21

    申请号：US14489368

    申请日：2014-09-17

    Applicant: Brain Corporation

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

    IPC: G06F19/00 ,  B25J13/00 ,  G05B15/02

    CPC classification number: B25J13/006 ,  G05B15/02 ,  G05B2219/2642 ,  Y10S901/03

    Abstract: Computerized appliances may be operated by users remotely. In one exemplary 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.

    APPARATUS AND METHODS FOR EVENT-TRIGGERED UPDATES IN PARALLEL NETWORKS
    7.
    发明申请
    APPARATUS AND METHODS FOR EVENT-TRIGGERED UPDATES IN PARALLEL NETWORKS 有权
    并行网络中事件触发更新的设备和方法

    公开(公告)号：US20140250036A1

    公开(公告)日：2014-09-04

    申请号：US14198446

    申请日：2014-03-05

    Applicant: BRAIN CORPORATION

    Inventor： Eugene M. Izhikevich ,  Botond Szatmary ,  Csaba Petre ,  Filip Piekniewski ,  Jayram Moorkanikara Nageswaran

    IPC: G06N3/10

    CPC classification number: G06N3/08 ,  G05B13/027 ,  G06N3/049 ,  G06N3/10

    Abstract: A simple format is disclosed and referred to as Elementary Network Description (END). The format can fully describe a large-scale neuronal model and embodiments of software or hardware engines to simulate such a model efficiently. The architecture of such neuromorphic engines is optimal for high-performance parallel processing of spiking networks with spike-timing dependent plasticity. The software and hardware engines are optimized to take into account short-term and long-term synaptic plasticity in the form of LTD, LTP, and STDP.

    Abstract translation: 公开了一种简单的格式，并被称为基本网络描述（END）。 该格式可以充分描述大规模神经元模型和软件或硬件引擎的实施例，以有效地模拟这种模型。 这种神经形态发动机的架构对于具有尖峰时间依赖可塑性的加标网络的高性能并行处理是最佳的。 软件和硬件引擎经过优化考虑了LTD，LTP和STDP形式的短期和长期突触可塑性。

    Systems and methods for predictive/reconstructive visual object tracker
    8.
    发明授权
    Systems and methods for predictive/reconstructive visual object tracker 有权

    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.

    Home animation apparatus and methods
    10.
    发明授权
    Home animation apparatus and methods 有权

    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.

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