摘要
介绍了一种基于三维激光雷达和深度图像的障碍物检测方法。首先,根据Velodyne HDL-32E激光雷达自身工作特性,将点云数据以矩阵方式表达,并表示为深度图像;然后,根据点云中各点的距离信息在深度图像横向上进行聚类;最后,在纵向上建立线性模型,对聚类点进行分类,划分出地面点集和障碍物点集。仿真实验结果表明:本方法能够抑制障碍物遮挡造成的误判,并能够很好地适应地形变化。
An obstacle detection method based on 3Dlaser scanner and range image is proposed for intelligent vehicle.First,the range image of one scan is established based on the Welodyne HDL-32 E laser scanner data.Then,according to the range image analysis,the point cloud in one row of the image is classified into several groups.Finally,the point clouds in different groups are detected by a linear model in column.Simulation reveals that using the proposed method,the rate of false detection caused by the obstacle lock is reduced,and this method well adapts to the terrain change.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2016年第2期360-365,共6页
Journal of Jilin University:Engineering and Technology Edition
基金
'973'国家重点基础研究发展计划项目(2012CB723801)
关键词
车辆工程
三维点云
障碍物检测
环境感知
vehicle engineering
3Dpoint clouds
obstacle detection
environmented perception
