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Map-Based Localization Method for Autonomous Vehicles Using 3D-LIDAR * * This work is supported in part by the National Natural Science Foundation of China under Grant No. 61473209.

机译:使用3D-LIDAR的自动驾驶汽车基于地图的定位方法 * < ce:footnote id =“ fn1”> * 国家自然科学基金会部分支持这项工作批准号为61473209的中国。

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Precise and robust localization is a significant task for autonomous vehicles in complex scenarios. The accurate position of autonomous vehicles is necessary for decision making and path planning. In this paper, a novel method is proposed to precisely locate the autonomous vehicle using a 3D-LIDAR sensor. First, a curb detection algorithm is performed. Next, a beam model is utilized to extract the contour of the multi-frame curbs. Then, the iterative closest point algorithm and two Kalman filters are employed to estimate the position of autonomous vehicles based on the high-precision map. Finally, experimental results demonstrate the accuracy and robustness of the proposed method.
机译:对于复杂场景中的自动驾驶汽车而言,精确,强大的定位是一项重要的任务。自主车辆的准确位置对于决策和路径规划至关重要。在本文中,提出了一种使用3D-LIDAR传感器精确定位自动驾驶车辆的新方法。首先,执行路缘检测算法。接下来,利用梁模型提取多帧路缘的轮廓。然后,采用迭代最近点算法和两个卡尔曼滤波器,基于高精度地图估计自动驾驶汽车的位置。最后,实验结果证明了该方法的准确性和鲁棒性。

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