COLLABORATIVE CREATION OF INDOOR MAPS
    21.
    发明申请

    公开(公告)号:US20170370728A1

    公开(公告)日:2017-12-28

    申请号:US15650747

    申请日:2017-07-14

    CPC classification number: G01C21/206

    Abstract: This disclosure provides techniques for the creation of maps of indoor spaces. In these techniques, an individual or a team with no mapping or cartography expertise can contribute to the creation of maps of buildings, campuses or cities. An indoor location system can track the location of contributors in the building. As they walk through indoor spaces, an application may automatically create a map based on data from motion sensors by both tracking the location of the contributors and also inferring building features such as hallways, stairways, and elevators based on the tracked contributors' motions as they move through a structure. With these techniques, the process of mapping buildings can be crowd sourced to a large number of contributors, making the indoor mapping process efficient and easy to scale up.

    Collaborative creation of indoor maps

    公开(公告)号:US09733091B2

    公开(公告)日:2017-08-15

    申请号:US14178605

    申请日:2014-02-12

    CPC classification number: G01C21/206

    Abstract: This disclosure provides techniques for the creation of maps of indoor spaces. In these techniques, an individual or a team with no mapping or cartography expertise can contribute to the creation of maps of buildings, campuses or cities. An indoor location system can track the location of contributors in the building. As they walk through indoor spaces, an application may automatically create a map based on data from motion sensors by both tracking the location of the contributors and also inferring building features such as hallways, stairways, and elevators based on the tracked contributors' motions as they move through a structure. With these techniques, the process of mapping buildings can be crowd sourced to a large number of contributors, making the indoor mapping process efficient and easy to scale up.

    METHODS RESOLVING THE ELEVATION OF A TRACKED PERSONNEL OR ASSETS
    24.
    发明申请
    METHODS RESOLVING THE ELEVATION OF A TRACKED PERSONNEL OR ASSETS 有权
    解决追踪人员或资产的方法的方法

    公开(公告)号:US20130332106A1

    公开(公告)日:2013-12-12

    申请号:US13916024

    申请日:2013-06-12

    CPC classification number: G01C5/06 G01C5/00 G01C21/206

    Abstract: Methods and systems are described for determining the elevation of tracked personnel or assets (trackees) that can take input from mounted sensors on each trackee (including barometric, inertial, magnetometer, radio frequency ranging and signal strength, light and GPS sensors), external constraints (including ranging constraints, feature constraints, and user corrections), and terrain elevation data. An example implementation of this method for determining elevation of persons on foot is described. But this method is not limited to computing elevation of personnel or to on foot movements.

    Abstract translation: 描述了用于确定跟踪人员或资产(跟踪者)的高度的方法和系统,可以从每个跟踪器上的安装的传感器(包括气压,惯性,磁力计,射频测距和信号强度,光和GPS传感器),外部约束 (包括测距约束,特征约束和用户校正)和地形高程数据。 描述了用于确定步行人员的仰角的该方法的示例性实现。 但这种方法并不限于人员的升高或脚步的运动。

    SYSTEM AND METHOD FOR LOCALIZING A TRACKEE AT A LOCATION AND MAPPING THE LOCATION USING INERTIAL SENSOR INFORMATION
    25.
    发明申请
    SYSTEM AND METHOD FOR LOCALIZING A TRACKEE AT A LOCATION AND MAPPING THE LOCATION USING INERTIAL SENSOR INFORMATION 有权
    在位置上定位轨道并使用惯性传感器信息映射位置的系统和方法

    公开(公告)号:US20130332064A1

    公开(公告)日:2013-12-12

    申请号:US13852649

    申请日:2013-03-28

    CPC classification number: G01C21/206 G01C21/00 G01C21/165 G01S19/13 G01S19/39

    Abstract: A system and method for recognizing features for location correction in Simultaneous Localization And Mapping operations, thus facilitating longer duration navigation, is provided. The system may detect features from magnetic, inertial, GPS, light sensors, and/or other sensors that can be associated with a location and recognized when revisited. Feature detection may be implemented on a generally portable tracking system, which may facilitate the use of higher sample rate data for more precise localization of features, improved tracking when network communications are unavailable, and improved ability of the tracking system to act as a smart standalone positioning system to provide rich input to higher level navigation algorithms/systems. The system may detect a transition from structured (such as indoors, in caves, etc.) to unstructured (such as outdoor) environments and from pedestrian motion to travel in a vehicle. The system may include an integrated self-tracking unit that can localize and self-correct such localizations.

    Abstract translation: 提供了一种用于在同时定位和映射操作中识别位置校正的特征的系统和方法,从而促进更长的持续时间导航。 该系统可以检测来自磁性,惯性,GPS,光传感器和/或可以与位置相关联并在重新访问时识别的其它传感器的特征。 特征检测可以在通常便携式的跟踪系统上实现,这可以促进使用更高的采样率数据来更精确地定位特征,当网络通信不可用时改进的跟踪以及跟踪系统作为智能独立的改进的能力 定位系统为更高级别的导航算法/系统提供丰富的输入。 系统可以检测从结构化(例如室内,洞穴等)到非结构化(例如室外)环境和从行人运动到车辆行驶的过渡。 该系统可以包括集成的自我跟踪单元,其可以本地化和自校正这样的定位。

    METHOD FOR STEP DETECTION AND GAIT DIRECTION ESTIMATION
    27.
    发明申请
    METHOD FOR STEP DETECTION AND GAIT DIRECTION ESTIMATION 审中-公开
    步骤检测方法和GAIT方向估计

    公开(公告)号:US20130311133A1

    公开(公告)日:2013-11-21

    申请号:US13791443

    申请日:2013-03-08

    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。

    VALIDATING AND UPDATING BUILDING MODELS WITH PATH DATA

    公开(公告)号:US20200372707A1

    公开(公告)日:2020-11-26

    申请号:US16989287

    申请日:2020-08-10

    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.

    METHODS FOR GENERATING AND UPDATING BUILDING MODELS

    公开(公告)号:US20200372706A1

    公开(公告)日:2020-11-26

    申请号:US16989212

    申请日:2020-08-10

    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.

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