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11 条记录 (耗时 0.014 秒)

    DETERMINING LOCALIZATION CONFIDENCE OF VEHICLES BASED ON CONVERGENCE RANGES
    1.
    发明申请
    DETERMINING LOCALIZATION CONFIDENCE OF VEHICLES BASED ON CONVERGENCE RANGES 有权

    公开(公告)号：US20210003403A1

    公开(公告)日：2021-01-07

    申请号：US16919150

    申请日：2020-07-02

    申请人： DeepMap Inc.

    发明人： Mark Wheeler ,  Derik Schroeter

    IPC分类号： G01C21/30

    摘要： According to an aspect of an embodiment, operations may comprise for each of the set of geographic X-positions, accessing an HD map of a geographical region surrounding the geographic X-position, determining a convergence range for the geographic X-position, and storing the convergence range for the geographic X-position in the HD map. The operations may also comprise accessing the HD map, predicting a next geographic X-position of a target vehicle, predicting a covariance of the predicted next geographic X-position, accessing the convergence range for the geographic X-position in the HD map closest to the predicted next geographic X-position, estimating a current geographic X-position of the target vehicle by performing a localization algorithm, and determining a confidence value for the estimated current geographic X-position of the target vehicle based on the predicted next geographic X-position, the predicted covariance, and the accessed convergence range.

    Identifying dynamic objects in a point cloud
    2.
    发明授权
    Identifying dynamic objects in a point cloud 有权

    公开(公告)号：US11151394B2

    公开(公告)日：2021-10-19

    申请号：US16910677

    申请日：2020-06-24

    申请人： DeepMap Inc.

    发明人： Derik Schroeter

    IPC分类号： G06K9/00 ,  G06T7/10 ,  G06T7/50 ,  G06T7/70 ,  G01C21/30 ,  G01S17/89 ,  G08G1/16

    摘要： Operations may comprise obtaining a first point cloud from a map representing a region. The operations may also include obtaining a second point cloud from one or more sensors of a vehicle traveling through the region. In addition, the operations may include identifying one or more subsets of clusters of second points of the second point cloud. The operations may also include determining correspondences between first points of the first point cloud and cluster points of the one or more subsets of clusters of the second point cloud. Moreover, the operations may include identifying at least a cluster of the one or more subsets of clusters, the identified cluster having, with respect to first points of the first point cloud, a correspondence percentage that is less than a threshold value. The operations may also include adjusting the second point cloud based on the identified cluster.

    Nearest neighbor search using compressed octrees representing high definition maps for autonomous vehicles
    3.
    发明授权
    Nearest neighbor search using compressed octrees representing high definition maps for autonomous vehicles 有权

    公开(公告)号：US11460580B2

    公开(公告)日：2022-10-04

    申请号：US16904238

    申请日：2020-06-17

    申请人： DeepMap Inc.

    发明人： Derik Schroeter

    IPC分类号： G06F16/2457 ,  G06F16/29 ,  G01S17/894 ,  G06F16/22 ,  G01C21/16 ,  G01S17/933 ,  G01S19/01

    摘要： According to an aspect of an embodiment, operations may comprise receiving a search query for points near a query-point, accessing a compressed octree representation of a point cloud comprising 3D points of a region, and traversing the compressed octree representation to identify regions that overlap a search space by, marking a current node as overlapping the search space responsive to determining that the current node is a leaf node, identifying a child node of the current node and performing a nearest neighbor search in the child node responsive to determining that a region represented by the current node overlaps the search space, and identifying a sibling node of the current node and performing the nearest neighbor search in the sibling node responsive to determining that a region represented by the current node does not overlap the search space.

    Image-based keypoint generation
    4.
    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.

    Determining localization confidence of vehicles based on convergence ranges
    6.
    发明授权
    Determining localization confidence of vehicles based on convergence ranges 有权

    公开(公告)号：US11340082B2

    公开(公告)日：2022-05-24

    申请号：US16919150

    申请日：2020-07-02

    申请人： DeepMap Inc.

    发明人： Mark Wheeler ,  Derik Schroeter

    IPC分类号： G01C21/32 ,  G01C21/36 ,  G06F16/29 ,  B60W60/00 ,  G01C21/30 ,  G06V20/56 ,  G05D1/00 ,  G05D1/02

    摘要： According to an aspect of an embodiment, operations may comprise for each of the set of geographic X-positions, accessing an HD map of a geographical region surrounding the geographic X-position, determining a convergence range for the geographic X-position, and storing the convergence range for the geographic X-position in the HD map. The operations may also comprise accessing the HD map, predicting a next geographic X-position of a target vehicle, predicting a covariance of the predicted next geographic X-position, accessing the convergence range for the geographic X-position in the HD map closest to the predicted next geographic X-position, estimating a current geographic X-position of the target vehicle by performing a localization algorithm, and determining a confidence value for the estimated current geographic X-position of the target vehicle based on the predicted next geographic X-position, the predicted covariance, and the accessed convergence range.

    REMOVAL OF EPHEMERAL POINTS FROM POINT CLOUD OF A HIGH-DEFINITION MAP FOR NAVIGATING AUTONOMOUS VEHICLES
    7.
    发明申请
    REMOVAL OF EPHEMERAL POINTS FROM POINT CLOUD OF A HIGH-DEFINITION MAP FOR NAVIGATING AUTONOMOUS VEHICLES 审中-公开

    公开(公告)号：US20200217964A1

    公开(公告)日：2020-07-09

    申请号：US16733143

    申请日：2020-01-02

    申请人： DeepMap Inc.

    发明人： Chen Chen ,  Liang Zou ,  Derik Schroeter ,  Mark Damon Wheeler

    IPC分类号： G01S17/89 ,  G05D1/00 ,  G05D1/02 ,  B60W60/00 ,  B60W50/00 ,  G06T19/00

    摘要： An autonomous vehicle system removes ephemeral points from lidar samples. The system receives a plurality of light detection and ranging (lidar) samples captured by a lidar sensor. Along with the lidar samples, the system receives an aligned pose and an unwinding transform for each of the lidar samples. The system determines one or more occupied voxel cells in a three-dimensional (3D) space using the lidar samples, their aligned poses, and their unwinding transforms. The system identifies occupied voxel cells representative of noise associated with motion of an object relative to the lidar sensor. The system filters the occupied voxel cells by removing the cells representative of noise. The system inputs the filtered occupied voxel cells in a 3D map comprising voxel cells, e.g., during the map generation and/or a map update.

    USING MEASURE OF CONSTRAINEDNESS IN HIGH DEFINITION MAPS FOR LOCALIZATION OF VEHICLES
    9.
    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.