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公开(公告)号：US20190244365A1
公开(公告)日：2019-08-08
申请号：US16357536
申请日：2019-03-19
Applicant: BRAIN CORPORATION
Inventor： Filip Piekniewski , Micah Richert , Dimitry Fisher , Patryk Laurent , Csaba Petre
CPC classification number: G06T7/20 , G06F12/08 , G06F2212/1016 , G06F2212/401 , G06T1/60 , G06T7/0002 , G06T9/00 , G06T9/002 , G06T9/004 , G06T2207/20084 , H04N19/503
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.
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公开(公告)号：US20180319015A1
公开(公告)日：2018-11-08
申请号：US16031950
申请日：2018-07-10
Applicant: Brain Corporation
Inventor： Oleg Sinyavskiy , Jean-Baptiste Passot , Patryk Laurent , Borja Ibarz Gabardos , Eugene Izhikevich
CPC classification number: B25J9/163 , B25J9/0081 , B25J9/1607 , B25J9/161 , B25J9/1666 , B25J9/1697 , G05D1/0088 , G05D1/0246 , G05D2201/02 , G06N3/00 , G06N3/008 , G06N3/049 , G06N99/005 , Y10S901/01 , Y10S901/03 , Y10S901/09 , Y10S901/47
Abstract: An apparatus and methods for training and/or operating a robotic device to perform a composite task comprising a plurality of subtasks. Subtasks may be arranged in a hierarchy. Individual tasks of the hierarchy may be operated by a respective learning controller. Individual learning controllers may interface to appropriate components of feature extractor configured to detect features in sensory input. Individual learning controllers may be trained to produce activation output based on occurrence of one or more relevant features and using training input. Output of a higher level controller may be provided as activation indication to one or more lower level controllers. Inactive activation indication may be utilized to deactivate one or more components thereby improving operational efficiency. Output of a given feature extractor may be shared between two or more learning controllers.
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公开(公告)号：US20180311817A1
公开(公告)日：2018-11-01
申请号：US15960300
申请日：2018-04-23
Applicant: Brain Corporation
Inventor： Patryk Laurent , Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Borja lbarz Gabardos , Eugene lzhikevich
CPC classification number: B25J9/163 , G05B2219/39271 , G05B2219/39289 , G06N3/008 , G06N3/049
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.
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公开(公告)号：US20180272529A1
公开(公告)日：2018-09-27
申请号：US15845832
申请日：2017-12-18
Applicant: Brain Corporation
Inventor： Filip Ponulak , Moslem Kazemi , Patryk Laurent , Oleg Sinyavskiy , Eugene Izhikevich
Abstract: 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：US09950426B2
公开(公告)日：2018-04-24
申请号：US15132003
申请日：2016-04-18
Applicant: BRAIN Corporation
Inventor： Patryk Laurent , Jean-Baptiste Passot , Oleg Sinyavskiy , Filip Ponulak , Borja Ibarz Gabardos , Eugene Izhikevich
CPC classification number: B25J9/163 , G05B2219/39271 , G05B2219/39289 , G06N3/008 , G06N3/049
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.
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Patent Agency Ranking
公开(公告)号：US09849588B2
公开(公告)日：2017-12-26
申请号：US14489242
申请日：2014-09-17
Applicant: Brain Corporation
Inventor： Eugene M. Izhikevich , Patryk Laurent , Csaba Petre , Todd Hylton , Vadim Polonichko
CPC classification number: B25J9/163 , B25J9/1697 , G05B15/02 , G05B2219/2642 , G05B2219/40411 , H04L12/2803 , H04L12/282 , H04L2012/2841 , H04L2012/2849 , Y10S901/05
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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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
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.
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公开(公告)号：US09821457B1
公开(公告)日：2017-11-21
申请号：US14595163
申请日：2015-01-12
Applicant: BRAIN CORPORATION
Inventor： Patryk Laurent , Jean-Baptiste Passot , Mark Wildie , Eugene M. Izhikevich , Vadim Polonichko
IPC: B25J9/16
CPC classification number: B25J9/161 , G05B19/409 , G05B2219/36136 , G05B2219/36137 , G06N3/049 , Y10S901/02 , Y10S901/28
Abstract: Apparatus and methods for training of robotic devices. 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. User interface of the remote controller may be reconfigured based on the detected phenotype and/or operational changes.
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公开(公告)号：US09789605B2
公开(公告)日：2017-10-17
申请号：US15174858
申请日：2016-06-06
Applicant: Brain Corporation
Inventor： Philip Meier , Jean-Baptiste Passot , Borja Ibarz Gabardos , Patryk Laurent , Oleg Sinyavskiy , Peter O'Connor , Eugene Izhikevich
CPC classification number: B25J9/163 , B25J9/1602 , B25J9/161 , B25J9/1656 , G05B2219/40116 , G05D1/0033 , G05D1/0088 , G05D2201/02 , G06N3/008 , G06N99/005 , Y10S901/01 , Y10S901/46
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.
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公开(公告)号：US20170232613A1
公开(公告)日：2017-08-17
申请号：US15464104
申请日：2017-03-20
Applicant: Brain Corporation
Inventor： Filip Ponulak , Moslem Kazemi , Patryk Laurent , Oleg Sinyavskiy , Eugene zhikevich
CPC classification number: B25J9/163 , B25J9/161 , G05B2219/36418 , G05B2219/36425 , G05B2219/40499 , G05D1/005 , G05D1/0088 , G05D1/0221 , G05D2201/02 , G06N3/008 , G06N3/049 , G06N99/005
Abstract: 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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