KUANG Wen-zhen， WU Meng-luo， XU Li
（School of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China）
Abstract： The detection of obstacles in a dynamic environment is a hot and difficult problem. A method of autonomously detecting obstacles based on laser radar is proposed as a safety auxiliary structure of tram. The nearest neighbor method is used for spatial obstacles clustering from laser radar data. By analyzing the characteristics of obstacles, the types of obstacles are determined by time correlation. Experiments were carried out on the developed unmanned aerial vehicle(UAV), and the experimental results verify the effectiveness of the proposed method.
Key words： laser radar; tram; dynamic obstacle detection; spatial obstacle clustering; time correlation; nearest neigbor method
CLD number： TP242.6 Document code： A
Article ID： 1674-8042（2018）04-0316-05 doi： 10.3969/j.issn.1674-8042.2018.04.002
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基于激光雷达的有轨电车动态障碍物检测
旷文珍， 吴梦萝， 许 丽
（兰州交通大学 自动化与电气工程学院， 甘肃 兰州 730070）
摘 要： 动态环境下的障碍物检测是目前研究的热点和难点。 本文提出了一种基于激光雷达的自主动态障碍物检测方法作为有轨电车的安全辅助结构。 通过近邻法对激光雷达测距数据进行空间障碍聚类， 在此基础上， 分析障碍物的特征， 利用时间关联性来确定障碍物类型。 在所研制的无人机上进行了实验， 实验结果验证了该方法的有效性。
关键词： 激光雷达； 有轨电车； 动态障碍物检测； 空间障碍聚类； 时间关联； 邻近算法
引用格式： KUANG Wen-zhen， WU Meng-luo， XU Li. Dynamic obstacles detection of tram based on laser radar. Journal of Measurement Science and Instrumentation, 2018, 9(4)： 316-320. ［doi： 10.3969／j.issn.1674-8042.2018.04.002］
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