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    Visualization of high definition map data
    3.
    发明授权
    Visualization of high definition map data 有权

    公开(公告)号：US11566903B2

    公开(公告)日：2023-01-31

    申请号：US16290480

    申请日：2019-03-01

    申请人： NVIDIA CORPORATION

    发明人： Gil Colgate ,  Mark Damon Wheeler ,  Wei Luo

    IPC分类号： G01C21/36 ,  G05D1/00 ,  G06T7/70 ,  G06T11/60 ,  G05D1/02 ,  G01C21/32 ,  G01C21/34 ,  G06V20/40 ,  G06V20/56 ,  G06V30/262

    摘要： The autonomous vehicle generates an overlapped image by overlaying HD map data over sensor data and rendering the overlaid images. The visualization process is repeated as the vehicle drives along the route. The visualization may be displayed on a screen within the vehicle or at a remote device. The system performs reverse rendering of a scene based on map data from a selected point. For each line of sight originating at the selected point, the system identifies the farthest object in the map data. Accordingly, the system eliminates objects obstructing the view of the farthest objects in the HD map as viewed from the selected point. The system further allows filtering of objects using filtering criteria based on semantic labels. The system generates a view from the selected point such that 3D objects matching the filtering criteria are eliminated from the view.

    ENCODING LIDAR SCANNED DATA FOR GENERATING HIGH DEFINITION MAPS FOR AUTONOMOUS VEHICLES
    5.
    发明申请
    ENCODING LIDAR SCANNED DATA FOR GENERATING HIGH DEFINITION MAPS FOR AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20220373687A1

    公开(公告)日：2022-11-24

    申请号：US17646293

    申请日：2021-12-28

    申请人： NVIDIA Corporation

    发明人： Lin Yang ,  Mark Damon Wheeler

    IPC分类号： G01S17/89 ,  H04N19/17 ,  G01C21/30 ,  G06T9/00 ,  G01S17/86 ,  G01S17/90 ,  G01S17/931 ,  G06V20/58 ,  G06V20/56 ,  G01C21/32 ,  G06T9/20

    摘要： Embodiments relate to methods for efficiently encoding sensor data captured by an autonomous vehicle and building a high definition map using the encoded sensor data. The sensor data can be LiDAR data which is expressed as multiple image representations. Image representations that include important LiDAR data undergo a lossless compression while image representations that include LiDAR data that is more error-tolerant undergo a lossy compression. Therefore, the compressed sensor data can be transmitted to an online system for building a high definition map. When building a high definition map, entities, such as road signs and road lines, are constructed such that when encoded and compressed, the high definition map consumes less storage space. The positions of entities are expressed in relation to a reference centerline in the high definition map. Therefore, each position of an entity can be expressed in fewer numerical digits in comparison to conventional methods.

    Directing board repositioning during sensor calibration for autonomous vehicles
    6.
    发明授权
    Directing board repositioning during sensor calibration for autonomous vehicles 有权

    公开(公告)号：US11482008B2

    公开(公告)日：2022-10-25

    申请号：US16920105

    申请日：2020-07-02

    申请人： NVIDIA CORPORATION

    发明人： Ziqiang Huang ,  Lin Yang ,  Mark Damon Wheeler

    IPC分类号： B60W60/00 ,  G06T7/73 ,  G06V20/56 ,  G01S17/931 ,  G01S7/481 ,  G01S7/497 ,  G01S17/10 ,  G01S17/89 ,  G01S17/894 ,  G06V10/75 ,  G05D1/02

    摘要： According to an aspect of an embodiment, operations may comprise determining a target position and orientation for a calibration board with respect to a camera of a vehicle, detecting a first position and orientation of the calibration board with respect to the camera of the vehicle, determining instructions for moving the calibration board from the first position and orientation to the target position and orientation, transmitting the instructions to a device, detecting a second position and orientation of the calibration board, determining whether the second position and orientation is within a threshold of matching the target position and orientation, and, in response to determining that the second position and orientation is within the threshold of matching the target position and orientation, capturing one or more calibration camera images using the camera and calibrating one or more sensors of the vehicle using the one or more calibration camera images.

    AUGMENTATION OF GLOBAL NAVIGATION SATELLITE SYSTEM BASED DATA
    9.
    发明申请
    AUGMENTATION OF GLOBAL NAVIGATION SATELLITE SYSTEM BASED DATA 有权

    公开(公告)号：US20230031260A1

    公开(公告)日：2023-02-02

    申请号：US17664653

    申请日：2022-05-23

    申请人： NVIDIA Corporation

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

    IPC分类号： G01C21/16 ,  G05D1/02 ,  G01S19/39 ,  G01S19/47 ,  G01S19/46 ,  G01S19/52 ,  G01C21/00

    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.