基于激光传感器的槽型轨轮廓匹配方法

为了实时掌握有轨电车线路的轨道状态，以期更有效地指导线路运营维护，针对有轨电车特殊的轨道结构和安装方式带来的轨道轮廓匹配困难问题，提出适用于槽型轨的轮廓匹配算法. 通过分析轨道的磨损规律及结构特征，定义槽型轨的匹配基准区域，给出区域的自动分割方法. 为了解决匹配区域定位困难的问题，设计两段式最近点迭代（ICP）匹配算法，实现轮廓的精确匹配；通过卡尔曼滤波器对匹配得到的旋转平移参数进行连续预测，解决在特殊情况下的异常匹配问题；通过实际线路实验，验证算法的可靠性. 实验结果表明：所提匹配算法具有快速、高精度和高鲁棒性的特点，能有效克服槽型轨的特殊结构和嵌入式安装方式带来的匹配困难问题.

Contour matching method of groove track based on laser sensor

Aiming at the difficulty of matching the special track structure and installation mode of the tram, a contour matching algorithm for embedded trough track was presented, in order to grasp the track status of tram lines in real time, and guide the line operation and maintenance more effectively. By analyzing the wear law and structural characteristics of the track, the matching reference area of the slotted rail was defined, and a automatic segmentation method of the region was presented. In order to solve the problem of the matching region locating, a two-step iterative closest point (ICP) matching algorithm was designed, which realized the exact matching of contour. The Kalman filter was used to predict the rotation and translation parameters to solve the problem of abnormal matching in special cases. The reliability of the algorithm was verified by actual line experiments. Experimental results show that the algorithm is fast, accurate and robust, and it can effectively overcome the matching difficulties caused by the special structure and embedded installation of groove rail.