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    OBJECT AND LOCATION TRACKING WITH A GRAPH-OF-GRAPHS
    1.
    发明申请
    OBJECT AND LOCATION TRACKING WITH A GRAPH-OF-GRAPHS 审中-公开

    公开(公告)号：US20190285417A1

    公开(公告)日：2019-09-19

    申请号：US16401685

    申请日：2019-05-02

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Jeffrey SIPKO ,  Kendall Clark YORK ,  John Benjamin HESKETH ,  Hubert VAN HOOF

    IPC: G01C21/20 ,  H04W4/38 ,  G06F16/29 ,  H04W4/33 ,  H04W4/80

    Abstract: A wearable device is configured with various sensory devices that recurrently monitor and gather data for a physical environment surrounding a user to help locate and track real-world objects. The various heterogeneous sensory devices digitize objects and the physical world. Each sensory device is configured with a threshold data change, in which, when the data picked up by one or more sensory devices surpasses the threshold, a query is performed on each sensor graph or sensory device. The queried sensor graph data is stored within a node in a spatial graph, in which nodes are connected to each other using edges to create spatial relationships between objects and spaces. Objects can be uploaded into an object graph associated with the spatial graph, in which the objects are digitized with each of the available sensors. This digital information can be subsequently used to, for example, locate the object.

    SHARING GEO-LOCATED INFORMATION
    4.
    发明申请
    SHARING GEO-LOCATED INFORMATION 审中-公开

    公开(公告)号：US20190342696A1

    公开(公告)日：2019-11-07

    申请号：US15972062

    申请日：2018-05-04

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Kenneth Liam KIEMELE ,  Donna Katherine LONG ,  Bryant Daniel HAWTHORNE ,  Anthony ERNST ,  Kendall Clark YORK ,  Jeffrey SIPKO ,  Janet Lynn SCHNEIDER ,  Christian Michael SADAK ,  Stephen G. LATTA

    IPC: H04W4/02

    Abstract: Examples are disclosed that relate to devices and methods for sharing geo-located information between different devices. In one example, a method comprises receiving the geo-located information from a first user device having a first data type compatible with a first output component of the device, receiving first sensor data from the first device, determining a location of the geo-located information within a coordinate system in a physical environment, determining that a second user device is located in the physical environment, determining that the second device does not comprise an output component that is compatible with the first data type, transforming the geo-located information into a second data type compatible with a second output component of the second device, determining that the second device is proximate to the location of the geo-located information, and sending the geo-located information to the second device for output by the second output component.

    USING A ONE-DIMENSIONAL RAY SENSOR TO MAP AN ENVIRONMENT
    8.
    发明申请
    USING A ONE-DIMENSIONAL RAY SENSOR TO MAP AN ENVIRONMENT 审中-公开

    公开(公告)号：US20190287296A1

    公开(公告)日：2019-09-19

    申请号：US15924025

    申请日：2018-03-16

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Jeffrey SIPKO ,  Kendall Clark YORK ,  John Benjamin HESKETH ,  Kenneth Liam KIEMELE ,  Bryant Daniel Hawthorne

    IPC: G06T17/05 ,  G01S17/89 ,  G01S7/481

    Abstract: A wearable device is configured with a one-dimensional depth sensor (e.g., a LIDAR system) that scans a physical environment, in which the wearable device and depth sensor generate a point cloud structure using scanned points of the physical environment to develop blueprints for a negative space of the environment. The negative space includes permanent structures (e.g., walls and floors), in which the blueprints distinguish permanent structures from temporary objects. The depth sensor is affixed in a static position on the wearable device and passively scans a room according to the gaze direction of the user. Over a period of days, weeks, months, or years the blueprint continues to supplement the point cloud structure and update points therein. Thus, as the user continues to navigate the physical environment, over time, the point cloud data structure develops an accurate blueprint of the environment.

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