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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：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：US11224971B2
公开(公告)日：2022-01-18
申请号：US16447261
申请日：2019-06-20
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：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
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：US09844873B2
公开(公告)日：2017-12-19
申请号：US15464104
申请日：2017-03-20
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：US20170001309A1
公开(公告)日：2017-01-05
申请号：US15200959
申请日：2016-07-01
申请人： BRAIN Corporation
发明人： Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Patryk Laurent , Borja Ibarz Gabardos , Eugene Izhikevich
摘要： 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
摘要翻译： 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
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公开(公告)号：US20150127150A1
公开(公告)日：2015-05-07
申请号：US14102410
申请日：2013-12-10
申请人： BRAIN CORPORATION
IPC分类号： B25J9/16
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.
摘要翻译： 机器人设备可以由训练者训练，该训练者使用与机器人的物理接触沿着目标轨迹引导机器人。 机器人可以包括自适应控制器，其被配置为基于训练者输入，感觉输入和/或性能测量中的一个或多个来产生控制命令。 训练者可以观察机器人执行任务。 响应于观察目标行为与实际行为之间的差异，培训者可以通过触觉动作提供教学输入。 机器人可以基于由机器人的学习过程产生的内部控制信号与训练输入的组合来执行动作。 机器人可以基于预测状态与机器人的实际状态的比较来推断教学输入。 机器人的学习过程可以根据教学输入进行调整，以减少后续试验期间的差异。
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公开(公告)号：US09008840B1
公开(公告)日：2015-04-14
申请号：US13866975
申请日：2013-04-19
申请人： Brain Corporation
CPC分类号： B25J9/163 , B25J9/161 , G05B13/0265 , G06N3/008 , G06N3/02 , G06N3/049 , G06N99/005
摘要： Framework may be implemented for transferring knowledge from an external agent to a robotic controller. In an obstacle avoidance/target approach application, the controller may be configured to determine a teaching signal based on a sensory input, the teaching signal conveying information associated with target action consistent with the sensory input, the sensory input being indicative of the target/obstacle. The controller may be configured to determine a control signal based on the sensory input, the control signal conveying information associated with target approach/avoidance action. The controller may determine a predicted control signal based on the sensory input and the teaching signal, the predicted control conveying information associated with the target action. The control signal may be combined with the predicted control in order to cause the robotic apparatus to execute the target action.
摘要翻译： 可以实现框架以将知识从外部代理传送到机器人控制器。 在避障/目标方法应用中，控制器可以被配置为基于感觉输入来确定教学信号，所述教学信号传达与感觉输入一致的目标动作相关联的信息，感觉输入指示目标/障碍物 。 控制器可以被配置为基于感觉输入来确定控制信号，所述控制信号传达与目标接近/回避动作相关联的信息。 控制器可以基于感觉输入和教学信号来确定预测的控制信号，预测的控制传达与目标动作相关联的信息。 控制信号可以与预测控制组合，以使机器人装置执行目标动作。
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公开(公告)号：US10369694B2
公开(公告)日：2019-08-06
申请号：US15960300
申请日：2018-04-23
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：US09384443B2
公开(公告)日：2016-07-05
申请号：US13918338
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
摘要： 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.
摘要翻译： 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。
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