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    SYSTEMS, APPARATUSES, AND METHODS FOR A DISTRIBUTED ROBOTIC NETWORK OF DATA COLLECTION AND INSIGHT GENERATION
    1.
    发明申请
    SYSTEMS, APPARATUSES, AND METHODS FOR A DISTRIBUTED ROBOTIC NETWORK OF DATA COLLECTION AND INSIGHT GENERATION 审中-公开

    公开(公告)号：WO2020206068A1

    公开(公告)日：2020-10-08

    申请号：PCT/US2020/026314

    申请日：2020-04-02

    Applicant: BRAIN CORPORATION

    Inventor： SZATMARY, Botond ,  ROSS, David

    IPC: H04L29/06

    Abstract: Systems, apparatuses, and methods for a distributed network of data collection and insight generation by server are disclosed herein. According to at least one non-limiting exemplary embodiment, the server may be configured to receive data from a network of data sources, receive an application from an application creator, and execute the application based on the data from the network of data sources to generate at least one insight, wherein the network of data sources may comprise mobile robots, stationary devices, IoT (Internet of Things) devices, and/or public data sources. The at least one insight may be utilized by robots to improve efficiency of operation or by humans to gain useful insights to the environment in which the data sources operate.

    SYSTEMS AND METHODS FOR DETECTION OF FEATURES WITHIN DATA COLLECTED BY A PLURALITY OF ROBOTS BY A CENTRALIZED SERVER
    4.
    发明申请
    SYSTEMS AND METHODS FOR DETECTION OF FEATURES WITHIN DATA COLLECTED BY A PLURALITY OF ROBOTS BY A CENTRALIZED SERVER 审中-公开

    公开(公告)号：WO2021003338A1

    公开(公告)日：2021-01-07

    申请号：PCT/US2020/040609

    申请日：2020-07-02

    Applicant: BRAIN CORPORATION

    Inventor： ROSS, David ,  SZATMARY, Botond

    IPC: G05B19/04 ,  G06N3/08 ,  G08G1/01

    Abstract: Systems and methods for detection of features within data collected by a plurality of robots by a centralized server are disclosed herein. According to at least one non-limiting exemplary embodiment, a plurality of robots may be utilized to collect a substantial amount of feature data using one or more sensors coupled thereto, wherein use of the plurality of robots to collect the feature data yields accurate localization of the feature data and consistent acquisition of the feature data. Systems and methods disclosed herein further enable a cloud server to identify a substantial number of features within the acquired feature data for purposes of generating insights. The substantial number of features far exceed a practical number of features of which a single neural network may be trained to identify.

    SYSTEMS AND METHODS FOR LOCALIZING DEVICES USING NETWORK SIGNATURES AND COVERAGE MAPS MEASURED BY ROBOTS
    5.
    发明申请
    SYSTEMS AND METHODS FOR LOCALIZING DEVICES USING NETWORK SIGNATURES AND COVERAGE MAPS MEASURED BY ROBOTS 审中-公开

    公开(公告)号：WO2021026427A1

    公开(公告)日：2021-02-11

    申请号：PCT/US2020/045352

    申请日：2020-08-07

    Applicant: BRAIN CORPORATION

    Inventor： ROSS, David ,  SZATMARY, Botond

    IPC: B25J9/16

    Abstract: Systems and methods for localizing devices using network signatures and coverage maps measured by robots are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot may generate a coverage map based on measurements collected during operation of the robot. The coverage map generated by the robot may be temporally accurate such that a device may be localized within the coverage map based on a received network signature from the device. The network signature comprising a measure of amplitudes of Wi-Fi networks and/or cellular networks at a point within an environment of the coverage map.

    SYSTEMS AND METHODS FOR TRAINING NEURAL NETWORKS ON A CLOUD SERVER USING SENSORY DATA COLLECTED BY ROBOTS
    7.
    发明申请
    SYSTEMS AND METHODS FOR TRAINING NEURAL NETWORKS ON A CLOUD SERVER USING SENSORY DATA COLLECTED BY ROBOTS 审中-公开

    公开(公告)号：WO2021097426A1

    公开(公告)日：2021-05-20

    申请号：PCT/US2020/060731

    申请日：2020-11-16

    Applicant: BRAIN CORPORATION

    Inventor： SZATMARY, Botond ,  ROSS, David

    IPC: G06N20/00 ,  G06N3/04 ,  G06N3/08

    Abstract: Systems and methods for training neural networks on a cloud server using sensory data collected by plurality of robots. According to at least one non-limiting exemplary embodiment, a system for training a model is disclosed. The model may be derived from one or more trained neural networks, the neural networks being trained using data collected by one or more robots. Advantageously, data collection by robots may enhance consistency, reliability, and quality of data received for use in training one or more neural networks. The model may be utilized by robots, upon sufficient training of the neural networks, such that the robots may identify features within their environments. Advantageously, the model may be trained on a cloud server and utilized by individual robots for use in enhancing autonomy of the robots, wherein the utilization of the model requires significantly fewer computational resources than training of the neural networks to develop the model.

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