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    VALIDATION OF GLOBAL NAVIGATION SATELLITE SYSTEM LOCATION DATA WITH OTHER SENSOR DATA
    3.
    发明申请
    VALIDATION OF GLOBAL NAVIGATION SATELLITE SYSTEM LOCATION DATA WITH OTHER SENSOR DATA 审中-公开

    公开(公告)号：US20200081134A1

    公开(公告)日：2020-03-12

    申请号：US16564303

    申请日：2019-09-09

    申请人： DeepMap Inc.

    发明人： Mark Damon Wheeler ,  Jeff Adachi ,  Chen Chen ,  Gregory William Coombe ,  Di Zeng

    IPC分类号： G01S19/39 ,  G01S19/47 ,  G01S19/46 ,  G01S19/52 ,  G05D1/02

    摘要： A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

    Image-based keypoint generation
    5.
    发明授权
    Image-based keypoint generation 有权

    公开(公告)号：US11367208B2

    公开(公告)日：2022-06-21

    申请号：US16912549

    申请日：2020-06-25

    申请人： DeepMap Inc.

    发明人： Ronghua Zhang ,  Derik Schroeter ,  Mengxi Wu ,  Di Zeng

    IPC分类号： G06T7/521 ,  G01C21/32 ,  G06T7/73 ,  G01S17/89

    摘要： Operations may comprise obtaining a plurality of light detection and ranging (LIDAR) scans of a region. The operations may also comprise identifying a plurality of LIDAR poses that correspond to the plurality of LIDAR scans. In addition, the operations may comprise identifying, as a plurality of keyframes, a plurality of images of the region that are captured during capturing of the plurality of LIDAR scans. The operations may also comprise determining, based on the plurality of LIDAR poses, a plurality of camera poses that correspond to the keyframes. Further, the operations may comprise identifying a plurality of two-dimensional (2D) keypoints in the keyframes. The operations also may comprise generating one or more three-dimensional (3D) keypoints based on the plurality of 2D keypoints and the respective camera poses of the plurality of keyframes.

    Validation of global navigation satellite system location data with other sensor data
    6.
    发明授权
    Validation of global navigation satellite system location data with other sensor data 有权

    公开(公告)号：US11340355B2

    公开(公告)日：2022-05-24

    申请号：US16564303

    申请日：2019-09-09

    申请人： DeepMap Inc.

    发明人： Mark Damon Wheeler ,  Jeff Adachi ,  Chen Chen ,  Gregory William Coombe ,  Di Zeng

    IPC分类号： G01S19/39 ,  G05D1/02 ,  G01S19/47 ,  G01S19/46 ,  G01S19/52 ,  G01C21/32

    摘要： A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

    USING MEASURE OF CONSTRAINEDNESS IN HIGH DEFINITION MAPS FOR LOCALIZATION OF VEHICLES
    8.
    发明申请
    USING MEASURE OF CONSTRAINEDNESS IN HIGH DEFINITION MAPS FOR LOCALIZATION OF VEHICLES 有权

    公开(公告)号：US20210003404A1

    公开(公告)日：2021-01-07

    申请号：US16919141

    申请日：2020-07-02

    申请人： DeepMap Inc.

    发明人： Di Zeng ,  Mengxi Wu ,  Derik Schroeter

    IPC分类号： G01C21/32 ,  G01C21/36 ,  B60W60/00 ,  G06K9/00 ,  G06F16/29

    摘要： According to an aspect of an embodiment, operations may comprise accessing a set of vehicle poses of one or more vehicles; for each of the set of vehicle poses, accessing a high definition (HD) map of a geographical region surrounding the vehicle pose, with the HD map comprising a three-dimensional (3D) representation of the geographical region, determining a measure of constrainedness for the vehicle pose, with the measure of constrainedness representing a confidence for performing localization for the vehicle pose based on 3D structures surrounding the vehicle pose, and storing the measure of constrainedness for the vehicle pose; and for each of the geographical regions surrounding each of the set of vehicle poses, determining a measure of constrainedness for the geographical region based on measures of constrainedness of vehicle poses within the geographical region, and storing the measure of constrainedness for the geographical region.