Method for step detection and gait direction estimation
    12.
    发明授权
    Method for step detection and gait direction estimation 有权
    步进检测和步态方向估计方法

    公开(公告)号:US08930163B2

    公开(公告)日:2015-01-06

    申请号:US13827506

    申请日:2013-03-14

    CPC classification number: G01C22/006 G06F17/10

    Abstract: A method for detecting a human's steps and estimating the horizontal translation direction and scaling of the resulting motion relative to an inertial sensor is described. When a pedestrian takes a sequence of steps the displacement can be decomposed into a sequence of rotations and translations over each step. A translation is the change in the location of pedestrian's center of mass and a rotation is the change along z-axis of the pedestrian's orientation. A translation can be described by a vector and a rotation by an angle.

    Abstract translation: 描述了一种用于检测人的步骤并估计相对于惯性传感器的所得运动的水平平移方向和缩放的方法。 当步行者采取一系列步骤时,可以通过每个步骤将位移分解成一系列旋转和翻译。 翻译是行人中心位置的变化,旋转是沿着行人方向的z轴的变化。 翻译可以通过向量和旋转来描述一个角度。

    METHODS FOR GENERATING AND UPDATING BUILDING MODELS

    公开(公告)号:US20220139031A1

    公开(公告)日:2022-05-05

    申请号:US17475935

    申请日:2021-09-15

    Abstract: Systems, methods and instructions for creating building models of physical structures is disclosed. The building model may be a collection of floors defined by outlines containing regions that may be offset relative to a main region, and a collection of connectors. Connectors may have connection points for tracking, routing and sizing. Connectors may indicate elevation changes through georeferenced structural features. Signal elements may also be features that provide corrections when tracking. Feature descriptors are data that describes the structural configuration and signal elements enabling them to be matched to previously collected data in a database. User interface elements assist a user of a tracking device in collecting floor information, structural features and signal features and validating certain collected information based on previously known information. The height of floors may also be inferred based on sensor data from the tracking device.

    Crowd sourced mapping with robust structural features

    公开(公告)号:US11268818B2

    公开(公告)日:2022-03-08

    申请号:US16387483

    申请日:2019-04-17

    Abstract: A location and mapping service is described that creates a global database of indoor navigation maps through crowd-sourcing and data fusion technologies. The navigation maps consist of a database of geo-referenced, uniquely described features in the multi-dimensional sensor space (e.g., including structural, RF, magnetic, image, acoustic, or other data) that are collected automatically as a tracked mobile device is moved through a building (e.g. a person with a mobile phone or a robot). The feature information can be used to create building models as one or more tracked devices traverse a building.

    Mapping complex building models
    15.
    发明授权

    公开(公告)号:US10740965B2

    公开(公告)日:2020-08-11

    申请号:US16428519

    申请日:2019-05-31

    Abstract: Systems, methods and instructions for creating building models of physical structures is disclosed. The building model may be a collection of floors defined by outlines containing regions that may be offset relative to a main region, and a collection of connectors. Connectors may have connection points for tracking, routing and sizing. Connectors may indicate elevation changes through georeferenced structural features. Signal elements may also be features that provide corrections when tracking. Feature descriptors are data that describes the structural configuration and signal elements enabling them to be matched to previously collected data in a database. User interface elements assist a user of a tracking device in collecting floor information, structural features and signal features and validating certain collected information based on previously known information. The height of floors may also be inferred based on sensor data from the tracking device.

    Crowd sourced mapping with robust structural features
    19.
    发明授权
    Crowd sourced mapping with robust structural features 有权
    拥有强大结构特征的人群采集映射

    公开(公告)号:US09395190B1

    公开(公告)日:2016-07-19

    申请号:US14714212

    申请日:2015-05-15

    CPC classification number: G01C21/206 G01C21/165 G01C21/32 G01S5/0252 G01S19/13

    Abstract: A location and mapping service is described that creates a global database of indoor navigation maps through crowd-sourcing and data fusion technologies. The navigation maps consist of a database of geo-referenced, uniquely described features in the multi-dimensional sensor space (e.g., including structural, RF, magnetic, image, acoustic, or other data) that are collected automatically as a tracked mobile device is moved through a building (e.g. a person with a mobile phone or a robot). The feature information can be used to create building models as one or more tracked devices traverse a building.

    Abstract translation: 描述了一个位置和地图服务,通过群众采集和数据融合技术创建了室内导航地图的全球数据库。 导航地图包括由跟踪的移动设备自动收集的多维传感器空间(例如,包括结构,RF,磁性,图像,声学或其他数据)中的地理参考的,独特描述的特征的数据库 移动通过建筑物(例如具有移动电话或机器人的人)。 当一个或多个跟踪设备穿过建筑物时,特征信息可用于创建建筑模型。

    METHOD TO SCALE INERTIAL LOCATION DATA USING DIRECTIONAL AND/OR SCALE CONFIDENCE CONSTRAINTS
    20.
    发明申请
    METHOD TO SCALE INERTIAL LOCATION DATA USING DIRECTIONAL AND/OR SCALE CONFIDENCE CONSTRAINTS 审中-公开
    使用方向和/或规模的信任约束来定量实际位置数据的方法

    公开(公告)号:US20140278080A1

    公开(公告)日:2014-09-18

    申请号:US14212529

    申请日:2014-03-14

    CPC classification number: G01C21/165 G01C21/08

    Abstract: Methods, systems, and computer readable storage media are presented for directional scaling of inertial path data to satisfy ranging constraints. The presented techniques take into account scaling confidence information. In addition to bounding potential scale corrections based on the reliability of the inertial path and the magnetic heading confidence, the techniques bound potential scale parameters based on constraints and solve for directional scale parameters.

    Abstract translation: 呈现方法,系统和计算机可读存储介质用于方向缩放惯性路径数据以满足测距约束。 所提出的技术考虑到置信信息的扩展。 除了基于惯性路径的可靠性和磁标题置信度的边界潜在尺度校正之外,这些技术基于约束约束了潜在的尺度参数,并且解决了定向尺度参数。

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