公开(公告)号：US09311594B1

公开(公告)日：2016-04-12

申请号：US13623838

申请日：2012-09-20

申请人： BRAIN CORPORATION

发明人： Dimitry Fisher ,  Eugene Izhikevich ,  Vadim Polonichko

IPC分类号： G06N5/00 ,  G06F1/00 ,  G06N3/04

CPC分类号： G06N3/049

摘要： Sensory encoder may be implemented. Visual encoder apparatus may comprise spiking neuron network configured to receive photodetector input. Excitability of neurons may be adjusted and output spike may be generated based on the input. When neurons generate spiking response, spiking threshold may be dynamically adapted to produce desired output rate. The encoder may dynamically adapt its input range to match statistics of the input and to produce output spikes at an appropriate rate and/or latency. Adaptive input range adjustment and/or spiking threshold adjustment collaborate to enable recognition of features in sensory input of varying dynamic range.

摘要翻译： 可以实现感觉编码器。 可视编码器装置可以包括配置成接收光电检测器输入的加标神经元网络。 可以调整神经元的兴奋性，并且可以基于输入产生输出尖峰。 当神经元产生尖峰响应时，尖峰阈值可以动态地适应以产生期望的输出速率。 编码器可以动态地调整其输入范围以匹配输入的统计量并以适当的速率和/或等待时间产生输出尖峰。 自适应输入范围调整和/或加标阈值调整协作可以识别不同动态范围的感官输入中的特征。

公开(公告)号：US11363929B2

公开(公告)日：2022-06-21

申请号：US16454199

申请日：2019-06-27

申请人： Brain Corporation

发明人： Botond Szatmary ,  Vadim Polonichko

IPC分类号： A47L9/28 ,  A47L9/00 ,  G05D1/02 ,  G06N3/00 ,  G06N3/04

摘要： Apparatus and methods for training and operating of robotic appliances. Robotic appliance may be operable to clean user premises. The user may train the appliance to perform cleaning operations in constrained areas. The appliance may be configured to clean other area of the premises automatically. The appliance may perform premises exploration and/or determine map of the premises. The appliance may be provided priority information associated with areas of the premises. The appliance may perform cleaning operations in order of the priority. Robotic vacuum cleaner appliance may be configured for safe cable operation wherein the controller may determine one or more potential obstructions (e.g., a cable) along operating trajectory. Upon approaching the cable, the controller may temporarily disable brushing mechanism in order to prevent cable damage.

公开(公告)号：US10376117B2

公开(公告)日：2019-08-13

申请号：US15665146

申请日：2017-07-31

申请人： Brain Corporation

发明人： Botond Szatmary ,  Vadim Polonichko

IPC分类号： A47L9/28 ,  A47L9/00 ,  G05D1/02 ,  G06N3/00 ,  G06N3/04

摘要： Apparatus and methods for training and operating of robotic appliances. Robotic appliance may be operable to clean user premises. The user may train the appliance to perform cleaning operations in constrained areas. The appliance may be configured to clean other area of the premises automatically. The appliance may perform premises exploration and/or determine map of the premises. The appliance may be provided priority information associated with areas of the premises. The appliance may perform cleaning operations in order of the priority. Robotic vacuum cleaner appliance may be configured for safe cable operation wherein the controller may determine one or more potential obstructions (e.g., a cable) along operating trajectory. Upon approaching the cable, the controller may temporarily disable brushing mechanism in order to prevent cable damage.

公开(公告)号：US20190143505A1

公开(公告)日：2019-05-16

申请号：US16199582

申请日：2018-11-26

申请人： Brain Corporation

发明人： Eugene Izhikevich ,  Dimitry Fisher ,  Jean-Baptiste Passot ,  Heathcliff Hatcher ,  Vadim Polonichko

IPC分类号： B25J9/16 ,  G06N20/00 ,  B25J13/08 ,  A63H3/20 ,  G06N3/00

摘要： Apparatus and methods for a modular robotic device with artificial intelligence that is receptive to training controls. In one implementation, modular robotic device architecture may be used to provide all or most high cost components in an autonomy module that is separate from the robotic body. The autonomy module may comprise controller, power, actuators that may be connected to controllable elements of the robotic body. The controller may position limbs of the toy in a target position. A user may utilize haptic training approach in order to enable the robotic toy to perform target action(s). Modular configuration of the disclosure enables users to replace one toy body (e.g., the bear) with another (e.g., a giraffe) while using hardware provided by the autonomy module. Modular architecture may enable users to purchase a single AM for use with multiple robotic bodies, thereby reducing the overall cost of ownership.

公开(公告)号：US20180260685A1

公开(公告)日：2018-09-13

申请号：US15785161

申请日：2017-10-16

申请人： Brain Corporation

发明人： Jean-Baptiste Passot ,  Oleg Sinyavskiy ,  Filip Ponulak ,  Patryk Laurent ,  Borja lbarz Gabardos ,  Eugene lzhikevich ,  Vadim Polonichko

IPC分类号： G06N3/04 ,  G06N3/00

CPC分类号： G06N3/049 ,  G06N3/008

摘要： 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.

公开(公告)号：US09613308B2

公开(公告)日：2017-04-04

申请号：US14244892

申请日：2014-04-03

申请人： BRAIN CORPORATION

发明人： Eugene M. Izhikevich ,  Patryk Laurent ,  Vadim Polonichko

IPC分类号： G05B19/418 ,  G05B19/04 ,  G05B19/18 ,  G06N3/00 ,  G06N3/04 ,  G06N99/00

CPC分类号： G06N3/008 ,  G05D1/0022 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/02 ,  G06N3/049 ,  G06N99/005 ,  Y10S901/01 ,  Y10S901/47

摘要： 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 associated 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.

公开(公告)号：US20160075018A1

公开(公告)日：2016-03-17

申请号：US14946589

申请日：2015-11-19

申请人： BRAIN Corporation

发明人： Eugene Izhikevich ,  Dimitry Fisher ,  Jean-Baptiste Passot ,  Heathcliff Hatcher ,  Vadim Polonichko

IPC分类号： B25J9/16 ,  B25J13/08

CPC分类号： B25J9/163 ,  A63H3/20 ,  B25J9/1694 ,  B25J13/08 ,  G06N3/008 ,  G06N3/049 ,  G06N99/005 ,  Y10S901/02 ,  Y10S901/04 ,  Y10S901/09 ,  Y10S901/50

摘要： Apparatus and methods for a modular robotic device with artificial intelligence that is receptive to training controls. In one implementation, modular robotic device architecture may be used to provide all or most high cost components in an autonomy module that is separate from the robotic body. The autonomy module may comprise controller, power, actuators that may be connected to controllable elements of the robotic body. The controller may position limbs of the toy in a target position. A user may utilize haptic training approach in order to enable the robotic toy to perform target action(s). Modular configuration of the disclosure enables users to replace one toy body (e.g., the bear) with another (e.g., a giraffe) while using hardware provided by the autonomy module. Modular architecture may enable users to purchase a single AM for use with multiple robotic bodies, thereby reducing the overall cost of ownership.

摘要翻译： 具有接受训练控制的人造智能的模块化机器人装置的装置和方法。 在一个实现中，模块化机器人设备架构可以用于在与机器人主体分离的自主模块中提供全部或最高成本的组件。 自主模块可以包括可以连接到机器人身体的可控元件的控制器，电源，致动器。 控制器可将玩具的四肢定位在目标位置。 用户可以利用触觉训练方法，以使机器人玩具能够执行目标动作。 本公开的模块化配置使得用户可以在使用由自主模块提供的硬件的同时，用另一个（例如，长颈鹿）来替换一个玩具体（例如熊）。 模块化架构可以使用户能够购买单个AM以用于多个机器人体，从而降低总拥有成本。

公开(公告)号：US20150258679A1

公开(公告)日：2015-09-17

申请号：US14209578

申请日：2014-03-13

申请人： Brain Corporation

发明人： Eugene Izhikevich ,  Dimitry Fisher ,  Jean-Baptiste Passot ,  Heathcliff Hatcher ,  Vadim Polonichko

IPC分类号： B25J9/00 ,  B25J13/00 ,  G06N99/00

CPC分类号： B25J9/0081 ,  A63H29/22 ,  A63H30/04 ,  B25J9/104 ,  B25J13/00 ,  G06N99/005 ,  Y10T74/20305 ,  Y10T74/20311 ,  Y10T74/20317

摘要： Apparatus and methods for a modular robotic device with artificial intelligence that is receptive to training controls. In one implementation, modular robotic device architecture may be used to provide all or most high cost components in an autonomy module that is separate from the robotic body. The autonomy module may comprise controller, power, actuators that may be connected to controllable elements of the robotic body. The controller may position limbs of the toy in a target position. A user may utilize haptic training approach in order to enable the robotic toy to perform target action(s). Modular configuration of the disclosure enables users to replace one toy body (e.g., the bear) with another (e.g., a giraffe) while using hardware provided by the autonomy module. Modular architecture may enable users to purchase a single AM for use with multiple robotic bodies, thereby reducing the overall cost of ownership.

摘要翻译： 具有接受训练控制的人造智能的模块化机器人装置的装置和方法。 在一个实现中，模块化机器人设备架构可以用于在与机器人主体分离的自主模块中提供全部或最高成本的组件。 自主模块可以包括可以连接到机器人身体的可控元件的控制器，电源，致动器。 控制器可将玩具的四肢定位在目标位置。 用户可以利用触觉训练方法，以使机器人玩具能够执行目标动作。 本公开的模块化配置使得用户可以在使用由自主模块提供的硬件的同时，用另一个（例如，长颈鹿）来替换一个玩具体（例如熊）。 模块化架构可以使用户能够购买单个AM以用于多个机器人体，从而降低总拥有成本。

公开(公告)号：US20140379624A1

公开(公告)日：2014-12-25

申请号：US13922143

申请日：2013-06-19

申请人： Brain Corporation

发明人： FILIP PIEKNIEWSKI ,  Vadim Polonichko ,  Eugene Izhikevich

IPC分类号： G06N3/02

CPC分类号： G06N3/08 ,  G06N3/049

摘要： Apparatus and methods for processing inputs by one or more neurons of a network. The neuron(s) may generate spikes based on receipt of multiple inputs. Latency of spike generation may be determined based on an input magnitude. Inputs may be scaled using for example a non-linear concave transform. Scaling may increase neuron sensitivity to lower magnitude inputs, thereby improving latency encoding of small amplitude inputs. The transformation function may be configured compatible with existing non-scaling neuron processes and used as a plug-in to existing neuron models. Use of input scaling may allow for an improved network operation and reduce task simulation time.

摘要翻译： 用于由网络的一个或多个神经元处理输入的装置和方法。 基于多个输入的接收，神经元可以产生尖峰。 可以基于输入幅度来确定尖峰生成的延迟。 可以使用例如非线性凹变换来缩放输入。 缩放可以将神经元灵敏度增加到较低幅度的输入，从而改善小振幅输入的延迟编码。 转换函数可以被配置为与现有的非缩放神经元过程兼容，并且用作现有神经元模型的插件。 使用输入缩放可以允许改进的网络操作并减少任务模拟时间。

公开(公告)号：US20140089232A1

公开(公告)日：2014-03-27

申请号：US13830398

申请日：2013-03-14

申请人： Brain Corporation

发明人： Marius Buibas ,  Eugene M. Izhikevich ,  Botond Szatmary ,  Vadim Polonichko

IPC分类号： G06N3/08

CPC分类号： G06N3/08 ,  G06N3/04 ,  G06N3/049 ,  G06N3/10

摘要： Apparatus and methods for learning and training in neural network-based devices. In one implementation, the devices each comprise multiple spiking neurons, configured to process sensory input. In one approach, alternate heterosynaptic plasticity mechanisms are used to enhance learning and field diversity within the devices. The selection of alternate plasticity rules is based on recent post-synaptic activity of neighboring neurons. Apparatus and methods for simplifying training of the devices are also disclosed, including a computer-based application. A data representation of the neural network may be imaged and transferred to another computational environment, effectively copying the brain. Techniques and architectures for achieve this training, storing, and distributing these data representations are also disclosed.

摘要翻译： 基于神经网络的设备学习和训练的装置和方法。 在一个实施方式中，每个装置包括多个加标神经元，其配置成处理感觉输入。 在一种方法中，使用交替的异质突触可塑性机制来增强装置内的学习和场分集。 替代可塑性规则的选择是基于最近邻近神经元的突触后活动。 还公开了用于简化设备训练的装置和方法，包括基于计算机的应用。 神经网络的数据表示可以被成像并传送到另一个计算环境，有效地复制大脑。 还公开了用于实现这种训练，存储和分发这些数据表示的技术和架构。