摘要
为了有效获取前方道路信息,应用于低成本的固态激光雷达,提出一种道路边沿与障碍物检测方法。首先对原始点云数据进行地面滤波处理,提取地面与非地面点云数据;根据地面点云数据中路沿高度突变的特征,提出了一种动态滑动窗口的方法提取路沿特征点,后使用随机抽样一致算法(random sample consensus,RANSAC)进行路沿直线拟合;将路沿内障碍物点云作为感兴趣区域(region of interest,ROI),在z轴方向上对障碍物点云数据进行安全高度为H直通滤波处理,最后使用欧氏聚类算法完成了对路沿内障碍物的检测。通过在校园内实际采集数据与处理实验,验证了该方法的可行性。
In order to effectively obtain the road information about the road ahead and apply it to the low-cost solid-state Lidar,a road edge and obstacle detection method is proposed in this paper.Firstly,ground filtering processes the original point cloud data to extract the ground and non-ground point cloud data.Based on the features of high mutation in the pastry cloud data,this paper proposes to extract the path feature points by dynamic sliding window,then uses random sampling consensus algorithm(RANSAC)to fit the inner obstacle point cloud as the region of interest(ROI),treats the obstacle point cloud data with H straight pass filter in the z-axis direction,and finally uses the European clustering algorithm.This paper verifies the feasibility of the method by conducting practical data acquisition and processing experiments on campus.
作者
王江
金永
姚慧栋
Wang Jiang;Jin Yong;Yao Huidong(School of Information and Communication Engineering,North University of China,Taiyuan 030051,China)
出处
《国外电子测量技术》
北大核心
2023年第1期138-143,共6页
Foreign Electronic Measurement Technology
基金
山西省省筹资金资助回国留学人员科研项目(2022-145)资助
关键词
固态激光雷达
三维点云
路沿检测
障碍物检测
solid-state lidar
3D point cloud
road edge detection
obstacle detection
