Patents by Inventor Filip Ponulak

Filip Ponulak has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10369694
    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.
    Type: Grant
    Filed: April 23, 2018
    Date of Patent: August 6, 2019
    Assignee: Brain Corporation
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Borja Ibarz Gabardos, Eugene Izhikevich
  • Publication number: 20180311817
    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.
    Type: Application
    Filed: April 23, 2018
    Publication date: November 1, 2018
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Borja lbarz Gabardos, Eugene lzhikevich
  • Publication number: 20180272529
    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.
    Type: Application
    Filed: December 18, 2017
    Publication date: September 27, 2018
    Inventors: Filip Ponulak, Moslem Kazemi, Patryk Laurent, Oleg Sinyavskiy, Eugene Izhikevich
  • Publication number: 20180260685
    Abstract: 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.
    Type: Application
    Filed: October 16, 2017
    Publication date: September 13, 2018
    Inventors: Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Patryk Laurent, Borja lbarz Gabardos, Eugene lzhikevich, Vadim Polonichko
  • Patent number: 9950426
    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.
    Type: Grant
    Filed: April 18, 2016
    Date of Patent: April 24, 2018
    Assignee: Brain Corporation
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Borja Ibarz Gabardos, Eugene Izhikevich
  • Patent number: 9844873
    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.
    Type: Grant
    Filed: March 20, 2017
    Date of Patent: December 19, 2017
    Assignee: Brain Corporation
    Inventors: Filip Ponulak, Moslem Kazemi, Patryk Laurent, Oleg Sinyavskiy, Eugene Izhikevich
  • Patent number: 9792546
    Abstract: 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.
    Type: Grant
    Filed: June 14, 2013
    Date of Patent: October 17, 2017
    Assignee: Brain Corporation
    Inventors: Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Patryk Laurent, Borja Ibarz Gabardos, Eugene Izhikevich, Vadim Polonichko
  • Publication number: 20170232613
    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.
    Type: Application
    Filed: March 20, 2017
    Publication date: August 17, 2017
    Inventors: Filip Ponulak, Moslem Kazemi, Patryk Laurent, Oleg Sinyavskiy, Eugene zhikevich
  • Patent number: 9597797
    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.
    Type: Grant
    Filed: December 10, 2013
    Date of Patent: March 21, 2017
    Assignee: Brain Corporation
    Inventors: Filip Ponulak, Moslem Kazemi, Patryk Laurent, Oleg Sinyavskiy, Eugene Izhikevich
  • Publication number: 20170001309
    Abstract: 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.
    Type: Application
    Filed: July 1, 2016
    Publication date: January 5, 2017
    Inventors: Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Patryk Laurent, Borja Ibarz Gabardos, Eugene Izhikevich
  • Publication number: 20160303738
    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.
    Type: Application
    Filed: April 18, 2016
    Publication date: October 20, 2016
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Borja Ibarz Gabardos, Eugene Izhikevich
  • Patent number: 9384443
    Abstract: 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.
    Type: Grant
    Filed: June 14, 2013
    Date of Patent: July 5, 2016
    Assignee: BRAIN CORPORATION
    Inventors: Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Patryk Laurent, Borja Ibarz Gabardos, Eugene Izhikevich
  • Patent number: 9314924
    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.
    Type: Grant
    Filed: June 14, 2013
    Date of Patent: April 19, 2016
    Assignee: Brain Corporation
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Oleg Sinyavskiy, Filip Ponulak, Borja Ibarz Gabardos, Eugene Izhikevich
  • Patent number: 9256215
    Abstract: Generalized state-dependent learning framework in artificial neuron networks may be implemented. A framework may be used to describe plasticity updates of neuron connections based on connection state term and neuron state term. The state connections within the network may be updated based on inputs and outputs to/from neurons. The input connections of a neuron may be updated using connection traces comprising a time-history of inputs provided via the connections. Weights of the connections may be updated and connection state may be time varying. The updated weights may be determined using a rate of change of the trace and a term comprising a product of a per-neuron contribution and a per-connection contribution configured to account for the state time-dependency. Using event-dependent connection change components, connection updates may be executed on per neuron basis, as opposed to per-connection basis.
    Type: Grant
    Filed: July 27, 2012
    Date of Patent: February 9, 2016
    Assignee: BRAIN CORPORATION
    Inventors: Oleg Sinyavskiy, Filip Ponulak
  • Patent number: 9248569
    Abstract: A robotic device may comprise an adaptive controller configured to learn to predict consequences of robotic device's actions. During training, the controller may receive a copy of the planned and/or executed motor command and sensory information obtained based on the robot's response to the command. The controller may predict sensory outcome based on the command and one or more prior sensory inputs. The predicted sensory outcome may be compared to the actual outcome. Based on a determination that the prediction matches the actual outcome, the training may stop. Upon detecting a discrepancy between the prediction and the actual outcome, the controller may provide a continuation signal configured to indicate that additional training may be utilized. In some classification implementations, the discrepancy signal may be used to indicate occurrence of novel (not yet learned) objects in the sensory input and/or indicate continuation of training to recognize said objects.
    Type: Grant
    Filed: November 22, 2013
    Date of Patent: February 2, 2016
    Assignee: Brain Corporation
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Filip Ponulak, Eugene Izhikevich
  • Patent number: 9213937
    Abstract: Apparatus and methods for universal node design implementing a universal learning rule in a mixed signal spiking neural network. In one implementation, at one instance, the node apparatus, operable according to the parameterized universal learning model, receives a mixture of analog and spiking inputs, and generates a spiking output based on the model parameter for that node that is selected by the parameterized model for that specific mix of inputs. At another instance, the same node receives a different mix of inputs, that also may comprise only analog or only spiking inputs and generates an analog output based on a different value of the node parameter that is selected by the model for the second mix of inputs. In another implementation, the node apparatus may change its output from analog to spiking responsive to a training input for the same inputs.
    Type: Grant
    Filed: February 6, 2013
    Date of Patent: December 15, 2015
    Assignee: BRAIN CORPORATION
    Inventor: Filip Ponulak
  • Patent number: 9156165
    Abstract: A control apparatus and methods using context-dependent difference learning for controlling e.g., a plant. In one embodiment, the apparatus includes an actor module and a critic module. The actor module provides a control signal for the plant. The actor module is subject to adaptation, which is performed to optimize control strategy of the actor. The adaptation is based upon the reinforcement signal provided by the critic module. The reinforcement signal is calculated based on the comparison of a present control performance signal observed for a certain context signal, with a control performance signal observed for the same context in the past.
    Type: Grant
    Filed: September 21, 2011
    Date of Patent: October 13, 2015
    Assignee: Brain Corporation
    Inventor: Filip Ponulak
  • Publication number: 20150148953
    Abstract: A robotic device may comprise an adaptive controller configured to learn to predict consequences of robotic device's actions. During training, the controller may receive a copy of the planned and/or executed motor command and sensory information obtained based on the robot's response to the command. The controller may predict sensory outcome based on the command and one or more prior sensory inputs. The predicted sensory outcome may be compared to the actual outcome. Based on a determination that the prediction matches the actual outcome, the training may stop. Upon detecting a discrepancy between the prediction and the actual outcome, the controller may provide a continuation signal configured to indicate that additional training may be utilized. In some classification implementations, the discrepancy signal may be used to indicate occurrence of novel (not yet learned) objects in the sensory input and/or indicate continuation of training to recognize said objects.
    Type: Application
    Filed: November 22, 2013
    Publication date: May 28, 2015
    Applicant: Brain Corporation
    Inventors: Patryk Laurent, Jean-Baptiste Passot, Filip Ponulak, Eugene Izhikevich
  • Publication number: 20150127150
    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.
    Type: Application
    Filed: December 10, 2013
    Publication date: May 7, 2015
    Applicant: BRAIN CORPORATION
    Inventors: Filip Ponulak, Moslem Kazemi, Patryk Laurent, Oleg Sinyavskiy, Eugene Izhikevich
  • Patent number: 9008840
    Abstract: 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.
    Type: Grant
    Filed: April 19, 2013
    Date of Patent: April 14, 2015
    Assignee: Brain Corporation
    Inventors: Filip Ponulak, Jean-Baptiste Passot, Eugene Izhikevich, Olivier Coenen