A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment.
A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment.
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DOI：
10.3390/s150921931
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发表时间：
2015-08-31
期刊：
影响因子：
--
通讯作者：
Chen X
中科院分区：
文献类型：
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作者：
Liu J;Liang H;Wang Z;Chen X
快速、准确地了解周围环境，包括路缘、车辆、行人等，是开发智能汽车的关键。这项工作中包含的道路元素是直接影响可驾驶区域的路缘和动态道路障碍物。本文介绍了一种利用多波束激光雷达，即以点云形式描述三维环境的Velodyne HDL64E型激光雷达对驾驶环境进行在线建模的框架。首先对Velodyne LIDAR采集的原始数据进行多特征提取，以满足在线环境建模的要求。对路缘和动态道路障碍物以不同的方式进行检测和跟踪。将为路缘点拟合曲线，并将点聚集到束中，计算其形状和运动学参数。卡尔曼滤波用于跟踪动态障碍物，而蛇形模型用于路缘。结果表明，该框架在各种环境下都具有较强的鲁棒性，能够满足在线处理的要求。
The quick and accurate understanding of the ambient environment, which is composed of road curbs, vehicles, pedestrians, etc., is critical for developing intelligent vehicles. The road elements included in this work are road curbs and dynamic road obstacles that directly affect the drivable area. A framework for the online modeling of the driving environment using a multi-beam LIDAR, i.e., a Velodyne HDL-64E LIDAR, which describes the 3D environment in the form of a point cloud, is reported in this article. First, ground segmentation is performed via multi-feature extraction of the raw data grabbed by the Velodyne LIDAR to satisfy the requirement of online environment modeling. Curbs and dynamic road obstacles are detected and tracked in different manners. Curves are fitted for curb points, and points are clustered into bundles whose form and kinematics parameters are calculated. The Kalman filter is used to track dynamic obstacles, whereas the snake model is employed for curbs. Results indicate that the proposed framework is robust under various environments and satisfies the requirements for online processing.