基于多线激光雷达的非结构化道路感知技术研究

Environment Perception Research Based on 3D-lidar in the Unstructured Road

为解决无人平台在越野条件下能够感知识别非结构化道路的问题,采用基于多线激光雷达的测距传感器检测技术,通过对激光点云数据做栅格化处理,并进行距地高度、高度差和梯度差等特征统计及聚类分析、目标跟踪,实现了对道路可通行区域、障碍物、坡道和动态车辆等的检测.结果表明,相比于相机,采用基于多线激光雷达的三维测距传感器检测技术,可以更直接地获取障碍物分布的位置信息,能够为无人平台的自主导航提供局部栅格地图.

To solve the accessible area detection under the unstructured road for unmanned ground vehicle,environment perception based on 3D-lidar is proposed. First,point clouds obtained from 3Dlidar are mapped to the grid-based map. Then statistics on features such as absolute height of point clouds,difference of height between adjacent point clouds and gradient difference are performed. After that,cluster analysis and object tracking will be used for road accessible area detection,obstacle detection,slope detection and dynamic vehicle detection and tracking. The results show that compared with the camera based method,the position of obstacles distribution can be directly obtained by point clouds based on 3D-lidar and a local grid-based map will be provided for autonomous navigation of unmanned ground vehicle.