基于激光雷达的道路环境障碍物检测方法

Method of Obstacle Detection on Road Environment Using LIDAR

激光雷达的环境感知是智能交通的一个关键环节。激光雷达以其数据量大、检测精度高等优点在该环节中发挥了重要作用。论文根据车体运动信息,对采集到的雷达数据进行数据转换、矫正,克服了高低起伏的路面带来的数据漂移问题;对矫正后的结果进行多密度聚类分析,得出障碍物信息;同时,基于雷达数据点的扫描角度和距离估计障碍物质心,根据相邻帧的惯导信息进行动态障碍物检测。在结构化道路环境中的实验结果表明所提出的方法对于单帧数据中的障碍物检测以及帧间的动态障碍物检测效果显著。

The environmental awareness of LIDAR is the key link in intelligent transportation. LIDAR with large amount of da. ta and high detection precision has played an important role. In this paper,according to the body movement information,the collect. ed LIDAR data are converted and corrected to overcome the data drift problem caused by high and low pavement. The results of the correction are analyzed by multi-density clustering to get the obstacle information. At the same time,based on the scanning angle and distance,the proposed method estimates the centroid of obstacles considering the inertial navigation information combined with the adjacent frame information to detect dynamic obstacles. The experimental results in the structured road environment show that the algorithms have significant improvement on the detection of obstacles in the single frame data and the dynamic obstacle detection between frames.