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公开(公告)号：US20220212342A1
公开(公告)日：2022-07-07
申请号：US17574760
申请日：2022-01-13
申请人： Brain Corporation
发明人： Patryk Laurent , Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Borja Ibarz Gabardos , Eugene Izhikevich
摘要： 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.
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公开(公告)号：US10295972B2
公开(公告)日：2019-05-21
申请号：US15143397
申请日：2016-04-29
申请人： Brain Corporation
发明人： Patryk Laurent , Eugene Izhikevich
摘要： 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.
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公开(公告)号：US10282849B2
公开(公告)日：2019-05-07
申请号：US15627096
申请日：2017-06-19
申请人： Brain Corporation
摘要： 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.
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公开(公告)号：US09597797B2
公开(公告)日：2017-03-21
申请号：US14102410
申请日：2013-12-10
申请人： BRAIN CORPORATION
CPC分类号： B25J9/163 , B25J9/161 , G05B2219/36418 , G05B2219/36425 , G05B2219/40499 , G05D1/005 , G05D1/0088 , G05D1/0221 , G05D2201/02 , G06N3/008 , G06N3/049 , G06N99/005
摘要： 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.
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公开(公告)号：US20150283701A1
公开(公告)日：2015-10-08
申请号：US14244892
申请日：2014-04-03
申请人： BRAIN CORPORATION
IPC分类号： B25J9/16
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 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.
摘要翻译： 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。
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6.发明申请APPARATUS AND METHODS FOR CONTROL OF ROBOT ACTIONS BASED ON CORRECTIVE USER INPUTS 有权基于正确的用户输入控制机器人动作的装置和方法公开(公告)号：US20150217449A1
公开(公告)日：2015-08-06
申请号：US14171762
申请日：2014-02-03
申请人： Brain Corporation
发明人： Philip Meier , Jean-Baptiste Passot , Borja Ibarz Gabardos , Patryk Laurent , Oleg Sinyavskiy , Peter O'Connor , Eugene Izhikevich
CPC分类号： B25J9/163 , B25J9/1602 , B25J9/161 , B25J9/1656 , G05B2219/40116 , G05D1/0033 , G05D1/0088 , G05D2201/02 , G06N3/008 , G06N99/005 , Y10S901/01 , Y10S901/46
摘要： 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.
摘要翻译： 机器人有能力执行广泛的有用任务，如工厂自动化，清洁，交付，辅助护理，环境监测和娱乐。 使机器人在新环境中执行新任务通常需要大量新的软件来编写，通常由专家小组编写。 如果未来的技术可以赋予人们对软件编码有限或不了解的机会来训练机器人来执行定制任务，这将是有价值的。 本发明的一些实施方案提供了响应于用户的校正命令以生成和改进用于基于传感器数据输入确定适当动作的策略的方法和系统。 完成学习后，系统可以通过从感官数据中导出控制命令来生成控制命令。 使用学习的控制策略，机器人可以自主行为。
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公开(公告)号：US20150032258A1
公开(公告)日：2015-01-29
申请号：US13953595
申请日：2013-07-29
申请人： BRAIN CORPORATION
IPC分类号： B25J9/16
CPC分类号： B25J9/1656 , G05B2219/35444 , G05B2219/40116 , G06N3/008 , G06N3/049
摘要： A robot may be trained based on cooperation between an operator and a trainer. During training, the operator may control the robot using a plurality of control instructions. The trainer may observe movements of the robot and generate a plurality of control commands, such as gestures, sound and/or light wave modulation. Control instructions may be combined with the trainer commands via a learning process in order to develop an association between the two. During operation, the learning process may generate one or more control instructions based on one or more gesture by the trainer. One or both the trainer or the operator may comprise a human, and/or computerized entity.
摘要翻译： 可以基于操作者和训练者之间的协作训练机器人。 在训练期间，操作员可以使用多个控制指令来控制机器人。 训练者可以观察机器人的运动并产生多个控制命令，例如手势，声音和/或光波调制。 控制指令可以通过学习过程与训练器命令组合，以便在两者之间建立关联。 在操作期间，学习过程可以基于训练者的一个或多个手势产生一个或多个控制指令。 训练者或操作员中的一个或两个可以包括人类和/或计算机化的实体。
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公开(公告)号：US09792546B2
公开(公告)日：2017-10-17
申请号：US13918298
申请日：2013-06-14
申请人： BRAIN CORPORATION
发明人： Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Patryk Laurent , Borja Ibarz Gabardos , Eugene Izhikevich , Vadim Polonichko
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.
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公开(公告)号：US09630317B2
公开(公告)日：2017-04-25
申请号：US14244888
申请日：2014-04-03
申请人： BRAIN CORPORATION
CPC分类号： B25J9/163 , B25J9/161 , G05D1/0022 , G05D1/0088 , G05D1/0246 , G05D2201/02 , G06N3/008 , G06N3/049 , G06N99/005
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.
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公开(公告)号：US20160303738A1
公开(公告)日：2016-10-20
申请号：US15132003
申请日：2016-04-18
申请人： BRAIN Corporation
发明人： Patryk Laurent , Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Borja Ibarz Gabardos , Eugene Izhikevich
IPC分类号： B25J9/16
CPC分类号： B25J9/163 , G05B2219/39271 , G05B2219/39289 , G06N3/008 , G06N3/049
摘要： 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.
摘要翻译： 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。
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