Tracking and modeling processing of image data for LiDAR-based vehicle tracking system and method

    公开(公告)号:US10984540B2

    公开(公告)日:2021-04-20

    申请号:US16160771

    申请日:2018-10-15

    Applicant: TUSIMPLE, INC.

    Inventor: Xue Mei Chenyang Li

    Abstract: A method of LiDAR-based vehicle tracking 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 including taking point clusters that belong to vehicles in a single LiDAR frame as input, tracking each vehicle as a probabilistic distribution, assigning each tracked vehicle to a corresponding one of the point clusters, and recalculating the probabilistic distribution of each tracked vehicle.

    System and method for vehicle position and velocity estimation based on camera and LIDAR data

    公开(公告)号:US11557128B2

    公开(公告)日:2023-01-17

    申请号:US16752637

    申请日:2020-01-25

    Applicant: TuSimple, Inc.

    Abstract: A vehicle position and velocity estimation based on camera and LIDAR data are disclosed. A particular embodiment includes: receiving input object data from a subsystem of an autonomous vehicle, the input object data including image data from an image generating device and distance data from a distance measuring device; determining a two-dimensional (2D) position of a proximate object near the autonomous vehicle using the image data received from the image generating device; tracking a three-dimensional (3D) position of the proximate object using the distance data received from the distance measuring device over a plurality of cycles and generating tracking data; determining a 3D position of the proximate object using the 2D position, the distance data received from the distance measuring device, and the tracking data; determining a velocity of the proximate object using the 3D position and the tracking data; and outputting the 3D position and velocity of the proximate object relative to the autonomous vehicle.

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