摘要
针对无人驾驶智能车道路检测问题,基于单线激光雷达的路面可行区域提取方法.依据激光雷达扫描点在可行路面的连续性,首先用相邻扫描点间的欧氏距离对点聚类,然后用加权移动平均值对每类点平滑滤波,再利用斜率将数据点分割成多段近似直线段,用最小二乘法对线段进行拟合.最后根据线段的斜率和长度、高程信息从多条线段中选取可行路面.实验结果证明,算法可以实时有效的从激光雷达扫描点中提取路面可行区域.
A drivable road regions detection method is proposed to identify the characteristics of the road for unmanned intelligent vehicles, which is mainly according to the continuity of LiDAR data on the road. First, the points are clustered by the distance between adjacent scanning points and using weighted moving average filter to smooth the points of each cluster. Then, the points are divided into several approximately straight line segments based on the slope from fitting a few consecutive points with the least square method, using the least square fitting line segments to obtain the slope of these line segments. Finally, the passable regions are selected from those line segments by means of their slope, length and elevation. Experimental results demonstrate that the proposed method provides real-time and reliable detection performance.
出处
《武汉理工大学学报（交通科学与工程版）》
2017年第2期203-207,共5页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家自然科学基金项目资助(51405359)
