越野环境下基于四线激光雷达的障碍检测

Obstacle Detection Based on a Four-layer Laser Radar in Cross-country

为了完成越野环境中无人自主导航车的障碍检测任务,应用四线激光雷达,提出了1种新的障碍检测算法,该算法利用检测区域的坡度信息进行障碍检测,包括坐标变换、候选障碍点提取、候选障碍点聚类及点簇高度求取4个步骤。为了克服激光雷达检测盲区与抑止测量过程中干扰噪声的影响,运用了卡尔曼滤波算法对目标障碍进行了滤波处理。试验结果表明,障碍检测算法稳定可靠。

In order to obtain obstacle information in a cross-country environment for an autonomous land vehicle （ALV）, a novel obstacle detection algorithm is proposed by using a four-layer laser radar LD_ML. The obstacle detection algorithm achieves the obstacle detection task by the gradient information of detection regions in four steps： （ 1 ） changing scanning points＇ coordinate system from the LD_ML to the ALV; （2） extracting candidate obstacles points from LD_ML range data; （3） clustering the candidate obstacle points; （4） obtaining the height information of candidate obstacle clustering. To overcome the blind detecting areas and the measurement noise of the LD_ML, Kalman filtering technology is used to estimate the position of obstacles and to track the obstacles. The experimental results show that the obstacle detection algorithm is reliable and robust.