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    Relaxation optimization model to plan an open space trajectory for autonomous vehicles
    6.
    发明授权
    Relaxation optimization model to plan an open space trajectory for autonomous vehicles 有权

    公开(公告)号：US11409284B2

    公开(公告)日：2022-08-09

    申请号：US16413315

    申请日：2019-05-15

    申请人： Baidu USA LLC

    发明人： Runxin He ,  Jinyun Zhou ,  Qi Luo ,  Shiyu Song ,  Jinghao Miao ,  Jiangtao Hu ,  Yu Wang ,  Jiaxuan Xu ,  Shu Jiang

    IPC分类号： G01C22/00 ,  G05D1/00 ,  G05D1/02 ,  G06F16/9537

    摘要： In one embodiment, an open space model is generated for a system to plan trajectories for an ADV in an open space. The system perceives an environment surrounding an ADV including one or more obstacles. The system determines a target function for the open space model based on constraints for the one or more obstacles and map information. The system iteratively, performs a first quadratic programming (QP) optimization on the target function based on a first trajectory while fixing a first set of variables, and performs a second QP optimization on the target function based on a result of the first QP optimization while fixing a second set of variables. The system generates a second trajectory based on results of the first and the second QP optimizations to control the ADV autonomously according to the second trajectory.

    Dynamic model with learning based localization correction system
    7.
    发明授权
    Dynamic model with learning based localization correction system 有权

    公开(公告)号：US11269329B2

    公开(公告)日：2022-03-08

    申请号：US16659040

    申请日：2019-10-21

    申请人： Baidu USA LLC

    发明人： Shu Jiang ,  Qi Luo ,  Jinghao Miao ,  Jiangtao Hu ,  Jiaxuan Xu ,  Jingao Wang ,  Yu Wang ,  Jinyun Zhou ,  Runxin He

    IPC分类号： G05D1/00 ,  G05D1/02 ,  G06N5/04

    摘要： In one embodiment, a set of parameters representing a first state of an autonomous driving vehicle (ADV) to be simulated and a set of control commands to be issued at a first point in time. In response, a localization predictive model is applied to the set of parameters to determine a first position (e.g., x, y) of the ADV. A localization correction model is applied to the set of parameters to determine a set of localization correction factors (e.g., Δx, Δy). The correction factors may represent the errors between the predicted position of the ADV by the localization predictive model and the ground truth measured by sensors of the vehicle. Based on the first position of the ADV and the correction factors, a second position of the ADV is determined as the simulated position of the ADV.

    Point clouds registration system for autonomous vehicles
    9.
    发明授权
    Point clouds registration system for autonomous vehicles 有权

    公开(公告)号：US11608078B2

    公开(公告)日：2023-03-21

    申请号：US16336858

    申请日：2019-01-30

    申请人： Baidu USA LLC ,  Baidu.com Times Technology (Beijing) Co., Ltd.

    发明人： Runxin He ,  Yong Xiao ,  Pengfei Yuan ,  Li Yu ,  Shiyu Song

    IPC分类号： B60W60/00 ,  G06V20/56

    摘要： In one embodiment, a system is disclosed for registration of point clouds for autonomous driving vehicles (ADV). The system receives a number of point clouds and corresponding poses from ADVs equipped with LIDAR sensors capturing point clouds of a navigable area to be mapped, where the point clouds correspond to a first coordinate system. The system partitions the point clouds and the corresponding poses into one or more loop partitions based on navigable loop information captured by the point clouds. For each of the loop partitions, the system applies an optimization model to point clouds corresponding to the loop partition to register the point clouds. They system merges the one or more loop partitions together using a pose graph algorithm, where the merged partitions of point clouds are utilized to perceive a driving environment surrounding the ADV.

    Updated point cloud registration pipeline based on ADMM algorithm for autonomous vehicles
    10.
    发明授权
    Updated point cloud registration pipeline based on ADMM algorithm for autonomous vehicles 有权

    公开(公告)号：US11521329B2

    公开(公告)日：2022-12-06

    申请号：US16692956

    申请日：2019-11-22

    申请人： Baidu USA LLC

    发明人： Runxin He ,  Shiyu Song ,  Li Yu ,  Wendong Ding ,  Pengfei Yuan

    IPC分类号： G06T7/33 ,  G06T7/73 ,  G05D1/00 ,  G01S19/45 ,  G01S17/89

    摘要： In one embodiment, a system and method for point cloud registration of LIDAR poses of an autonomous driving vehicle (ADV) is disclosed. The method selects poses of the point clouds that possess higher confidence level during the data capture phase as fixed anchor poses. The fixed anchor points are used to estimate and optimize the poses of non-anchor poses during point cloud registration. The method may partition the points clouds into blocks to perform the ICP algorithm for each block in parallel by minimizing the cost function of the bundle adjustment equation updated with a regularity term. The regularity term may measure the difference between current estimates of the poses and previous or the initial estimates. The method may also minimize the bundle adjustment equation updated with a regularity term when solving the pose graph problem to merge the optimized poses from the blocks to make connections between the blocks.