MULTI-SENSOR COLLABORATIVE CALIBRATION SYSTEM

    公开(公告)号:US20240241515A1

    公开(公告)日:2024-07-18

    申请号:US18621904

    申请日:2024-03-29

    Applicant: TUSIMPLE, INC.

    Abstract: Technique for performing multi-sensor collaborative calibration on a vehicle is disclosed. A method includes obtaining, from at least two sensors located on a vehicle, sensor data items of an area that comprises a plurality of calibration objects; determining, from the sensor data items, attributes of the plurality of calibration objects; determining, for the at least two sensors, an initial matrix that describes a first set of extrinsic parameters between the at least two sensors based at least on the attributes of the plurality of calibration objects; determining an updated matrix that describes a second set of extrinsic parameters between the at least two sensors based at least on the initial matrix and a location of at least one calibration object; and performing autonomous operation of the vehicle using the second set of extrinsic parameters and additional sensor data received from the at least two sensors.

    CAMERA POSE ESTIMATION TECHNIQUES

    公开(公告)号:US20210319584A1

    公开(公告)日:2021-10-14

    申请号:US17225396

    申请日:2021-04-08

    Applicant: TUSIMPLE, INC.

    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.

    CAMERA POSE ESTIMATION TECHNIQUES
    4.
    发明公开

    公开(公告)号:US20230410363A1

    公开(公告)日:2023-12-21

    申请号:US18461625

    申请日:2023-09-06

    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.

    LANE MARKING LOCALIZATION AND FUSION
    5.
    发明公开

    公开(公告)号:US20230408264A1

    公开(公告)日:2023-12-21

    申请号:US18456015

    申请日:2023-08-25

    Applicant: TuSimple, Inc.

    CPC classification number: G01C21/30

    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.

    MULTI-SENSOR COLLABORATIVE CALIBRATION SYSTEM

    公开(公告)号:US20220155776A1

    公开(公告)日:2022-05-19

    申请号:US16953089

    申请日:2020-11-19

    Applicant: TUSIMPLE, INC.

    Abstract: Technique for performing multi-sensor collaborative calibration on a vehicle is disclosed. A method includes obtaining, from at least two sensors located on a vehicle, sensor data items of an area that comprises a plurality of calibration objects; determining, from the sensor data items, attributes of the plurality of calibration objects; determining, for the at least two sensors, an initial matrix that describes a first set of extrinsic parameters between the at least two sensors based at least on the attributes of the plurality of calibration objects; determining an updated matrix that describes a second set of extrinsic parameters between the at least two sensors based at least on the initial matrix and a location of at least one calibration object; and performing autonomous operation of the vehicle using the second set of extrinsic parameters and additional sensor data received from the at least two sensors.

    PERCEPTION SYSTEM FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20250014305A1

    公开(公告)日:2025-01-09

    申请号:US18891113

    申请日:2024-09-20

    Applicant: TUSIMPLE, INC.

    Abstract: Image processing techniques are described to obtain an image from a camera located on a vehicle while the vehicle is being driven, cropping a portion of the obtained image corresponding to a region of interest, detecting an object in the cropped portion, adding a bounding box around the detected object, determining position(s) of reference point(s) on the bounding box, and determining a location of the detected object in a spatial region where the vehicle is being driven based on the determined one or more positions of the second set of one or more reference points on the bounding box.

    PERCEPTION SYSTEM FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20210397857A1

    公开(公告)日:2021-12-23

    申请号:US16909950

    申请日:2020-06-23

    Applicant: TUSIMPLE, INC.

    Abstract: Image processing techniques are described to obtain an image from a camera located on a vehicle while the vehicle is being driven, cropping a portion of the obtained image corresponding to a region of interest, detecting an object in the cropped portion, adding a bounding box around the detected object, determining position(s) of reference point(s) on the bounding box, and determining a location of the detected object in a spatial region where the vehicle is being driven based on the determined one or more positions of the second set of one or more reference points on the bounding box.

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