San Diego, CA, United States
San Diego, CA, United States

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Patent
Brain Corporation | Date: 2015-12-07

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.


Patent
Brain Corporation | Date: 2015-12-03

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.


Patent
Brain Corporation | Date: 2016-07-01

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 robots 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, users knowledge may be transferred to the robots controller to enable task execution in absence of subsequent inputs from the user


Patent
Brain Corporation | Date: 2015-06-24

Apparatus and methods for navigation of a robotic device configured to operate in an environment comprising objects and/or persons. Location of objects and/or persons may changed prior and/or during operation of the robot. In one embodiment, a bistatic sensor comprises a transmitter and a receiver. The receiver may be spatially displaced from the transmitter. The transmitter may project a pattern on a surface in the direction of robot movement. In one variant, the pattern comprises an encoded portion and an information portion. The information portion may be used to communicate information related to robot movement to one or more persons. The encoded portion may be used to determine presence of one or more object in the path of the robot. The receiver may sample a reflected pattern and compare it with the transmitted pattern. Based on a similarity measure breaching a threshold, indication of object present may be produced.


Patent
Brain Corporation | Date: 2015-06-26

Apparatus and methods for navigation of a robotic device configured to operate in an environment comprising objects and/or persons. Location of objects and/or persons may change prior and/or during operation of the robot. In one embodiment, a bistatic sensor comprises a transmitter and a receiver. The receiver may be spatially displaced from the transmitter. The transmitter may project a pattern on a surface in the direction of robot movement. In one variant, the pattern comprises an encoded portion and an information portion. The information portion may be used to communicate information related to robot movement to one or more persons. The encoded portion may be used to determine presence of one or more object in the path of the robot. The receiver may sample a reflected pattern and compare it with the transmitted pattern. Based on a similarity measure breaching a threshold, indication of object present may be produced.


Broadband signal transmissions may be used for object detection and/or ranging. Broadband transmissions may comprise a pseudo-random bit sequence or a bit sequence produced using, a random process. The sequence may be used to modulate transmissions of a given wave type. Various types of waves may be utilized, pressure, light, and radio waves. Waves reflected by objects within the sensing volume may be sampled. The received signal may be convolved with a time-reversed copy of the transmitted random sequence to produce a correlogram. The correlogram may be analyzed to determine range to objects. The analysis may comprise determination of one or more peaks/troughs in the correlogram. Range to an object may be determines based on a time lag of a respective peak.


Patent
Brain Corporation | Date: 2016-04-18

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 robots 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.


Apparatus and methods for detecting and utilizing saliency in digital images. In one implementation, salient objects may be detected based on analysis of pixel characteristics. Least frequently occurring pixel values may be deemed as salient. Pixel values in an image may be compared to a reference. Color distance may be determined based on a difference between reference color and pixel color. Individual image channels may be scaled when determining saliency in a multi-channel image. Areas of high saliency may be analyzed to determine object position, shape, and/or color. Multiple saliency maps may be additively or multiplicative combined in order to improve detection performance (e.g., reduce number of false positives). Methodologies described herein may enable robust tracking of objects utilizing fewer determination resources. Efficient implementation of the methods described below may allow them to be used for example on board a robot (or autonomous vehicle) or a mobile determining platform.


Patent
Brain Corporation | Date: 2015-03-03

Apparatus and methods for detecting and utilizing saliency in digital images. In one implementation, salient objects may be detected based on analysis of pixel characteristics. Least frequently occurring pixel values may be deemed as salient. Pixel values in an image may be compared to a reference. Color distance may be determined based on a difference between reference color and pixel color. Individual image channels may be scaled when determining saliency in a multi-channel image. Areas of high saliency may be analyzed to determine object position, shape, and/or color. Multiple saliency maps may be additively or multiplicative combined in order to improve detection performance (e.g., reduce number of false positives). Methodologies described herein may enable robust tracking of objects utilizing fewer determination resources. Efficient implementation of the methods described below may allow them to be used for example on board a robot (or autonomous vehicle) or a mobile determining platform.


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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