PEDESTRIAN DEAD RECKONING ESTIMATION FOR DIFFERENT DEVICE PLACEMENTS

    公开(公告)号:US20240401954A1

    公开(公告)日:2024-12-05

    申请号:US18731060

    申请日:2024-05-31

    Applicant: Apple Inc.

    Abstract: Embodiments are disclosed for PDR for different device placements. In some embodiments, a method comprises: obtaining motion data from a motion sensor of a mobile device; determining pedestrian or non-pedestrian class based on the device motion data; determining a placement of the device based on the device motion data; estimating a first direction of travel based on multiple direction of travel sources and the device placement; estimating a first velocity based on the pedestrian or non-pedestrian classification, the first estimate of direction of travel and a first estimate of speed; estimating a second velocity based on a kinematic model and the device motion data; selecting the first estimated velocity or the second estimated velocity based on selection logic; and determining a relative position of the device based on the selected estimated velocity.

    PEDESTRIAN DEAD RECKONING USING DIFFERENTIAL GEOMETRIC PROPERTIES OF HUMAN GAIT

    公开(公告)号:US20240094000A1

    公开(公告)日:2024-03-21

    申请号:US18240230

    申请日:2023-08-30

    Applicant: Apple Inc.

    CPC classification number: G01C21/12 G01C21/206

    Abstract: In some embodiments, a method comprises: receiving acceleration data from a motion sensor of a mobile device carried by a user, the acceleration data represented by a space curve in a three-dimensional (3D) acceleration space, the space curve indicative of a cyclical vertical displacement of the user's center of mass accompanied by a lateral left and right sway of the center of mass when the user is stepping; computing a tangent-normal-binormal (TNB) reference frame from the acceleration data, the TNB reference frame describing instantaneous geometric and kinematic properties of the space curve over time; and computing a direction of travel of the user based on an orientation of a unit binormal (B) vector of the TNB reference frame in the 3D acceleration space, and computing a speed of the user based on a linear regression model applied to the kinematic properties of the TNB reference frame.

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