Camera pose estimation techniques
    11.
    发明授权

    公开(公告)号:US11810322B2

    公开(公告)日:2023-11-07

    申请号:US17225396

    申请日:2021-04-08

    Applicant: TUSIMPLE, INC.

    CPC classification number: G06T7/74 G06T2207/30244 G06T2207/30256

    Abstract: Techniques are described for estimating pose of a camera located on a vehicle. An exemplary method of estimating camera pose includes obtaining, from a camera located on a vehicle, an image including a lane marker on a road on which the vehicle is driven, and estimating a pose of the camera such that the pose of the camera provides a best match according to a criterion between a first position of the lane marker determined from the image and a second position of the lane marker determined from a stored map of the road.

    System and method for proximate vehicle intention prediction for autonomous vehicles

    公开(公告)号:US11104334B2

    公开(公告)日:2021-08-31

    申请号:US15994138

    申请日:2018-05-31

    Applicant: TuSimple, Inc.

    Abstract: A system and method for proximate vehicle intention prediction for autonomous vehicles are disclosed. A particular embodiment is configured to: receive perception data associated with a host vehicle; extract features from the perception data to detect a proximate vehicle in the vicinity of the host vehicle; generate a trajectory of the detected proximate vehicle based on the perception data; use a trained intention prediction model to generate a predicted intention of the detected proximate vehicle based on the perception data and the trajectory of the detected proximate vehicle; use the predicted intention of the detected proximate vehicle to generate a predicted trajectory of the detected proximate vehicle; and output the predicted intention and predicted trajectory for the detected proximate vehicle to another subsystem.

    Lane marking localization and fusion

    公开(公告)号:US11009356B2

    公开(公告)日:2021-05-18

    申请号:US16184926

    申请日:2018-11-08

    Applicant: TuSimple, Inc.

    Abstract: Various embodiments of the present disclosure provide a system and method for iterative lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In an embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a plurality of cameras; and a computer connected to the locating device, database, and cameras, wherein the computer is adapted to receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information from the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and iteratively generate a predicted vehicle location based on the comparison of the response map and the region map.

    Post-processing module system and method for motioned-based lane detection with multiple sensors

    公开(公告)号:US10482769B2

    公开(公告)日:2019-11-19

    申请号:US15683494

    申请日:2017-08-22

    Applicant: TUSIMPLE

    Abstract: A method of visual odometry for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs include instructions, which when executed by a computing device, cause the computing device to perform the following steps comprising: receiving a lane marking, expressed in god's view, associated with a current view; fitting, in a post-processing module, the lane marking in an arc by using a set of parameters; generating a lane template, using the set of parameters, the lane template including features of the lane marking associated with the current view and features of the arc; and feeding the lane template associated with the current view for detection of a next view.

    Verification module system and method for motion-based lane detection with multiple sensors

    公开(公告)号:US12276516B2

    公开(公告)日:2025-04-15

    申请号:US18449340

    申请日:2023-08-14

    Applicant: TuSimple, Inc.

    Abstract: A method of lane detection for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs include instructions, which when executed by a computing device, cause the computing device to perform the following steps comprising: generating a ground truth associated with lane markings expressed in god's view; receiving features from at least one of a hit-map image and a fitted lane marking, wherein the hit-map image includes a classification of pixels that hit a lane marking, and the fitted lane marking includes pixels optimized based on the hit-map image; and training a confidence module based on the features and the ground truth, the confidence module configured to determine on-line whether a fitted lane marking is reasonable, using parameters that express a lane marking in an arc.

    Lane marking localization and fusion

    公开(公告)号:US12270661B2

    公开(公告)日:2025-04-08

    申请号:US18456015

    申请日:2023-08-25

    Applicant: TUSIMPLE, INC.

    Abstract: Various embodiments provide a system and method for iterative lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In an embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a plurality of cameras; and a computer connected to the locating device, database, and cameras, wherein the computer is adapted to receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information from the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and iteratively generate a predicted vehicle location based on the comparison of the response map and the region map.

    Lane Marking Localization
    18.
    发明申请

    公开(公告)号:US20200271473A1

    公开(公告)日:2020-08-27

    申请号:US15896077

    申请日:2018-02-14

    Applicant: TuSimple, Inc.

    Abstract: Various embodiments of the present disclosure provide a system and method for lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In an embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a camera; and a computer connected to the locating device, database, and camera, wherein the computer is adapted to: receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information from the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and generate a predicted vehicle location based on the comparison of the response map and the region map.

    LANE MARKING LOCALIZATION AND FUSION
    19.
    发明申请

    公开(公告)号:US20200271453A1

    公开(公告)日:2020-08-27

    申请号:US16184926

    申请日:2018-11-08

    Applicant: TuSimple, Inc.

    Abstract: Various embodiments of the present disclosure provide a system and method for iterative lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In an embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a plurality of cameras; and a computer connected to the locating device, database, and cameras, wherein the computer is adapted to receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information from the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and iteratively generate a predicted vehicle location based on the comparison of the response map and the region map.

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