基于双目立体视觉的列车目标识别和测距技术

随着近几年铁路运输量的大幅度提升，铁路运输自动化被提上了日程，现如今火车的调车与编组的效率都有了大幅度提高，但是，火车的摘钩分解操作依旧是需要人工完成.针对摘钩作业时间短，需要在机器人和车厢同步时准确识别目标把手和测距的问题，提出使用双目立体视觉技术配合机械臂自动摘取车钩的方法并对视觉部分进行深入研究:通过图像预处理和模板匹配技术识别目标把手，在利用特征检测和匹配算法恢复双目摄像机间的位姿信息，并对双目摄像机的位姿信息进行校正.为了克服立体匹配时光照不均的影响，提出了基于局部融合的立体匹配算法获取视差图，最后使用三角测量计算列车分解区域中目标把手的深度信息，实现三维重建.此方法可以在识别把手位置后，测量把手距双目视觉系统的物理距离，为机器人自动摘钩提供数据基础.

Train Target Recognition and Ranging Technology Based on Binocular Stereoscopic Vision

With the substantial increase of railway transportation volume in recent years， railway transportation automation has been scheduled. Nowadays， the efficiency of train shunting and marshalling has been greatly improved. However， the unhooking and decomposition operation of trains still need to be completed manually. In view of short time unhooking operation and the need to accurately identify the target handle and ranging when the robot is synchronized with the carriage， a method of automatic unhooking using binocular stereoscopic vision technology combined with the manipulator is proposed， and the vision part is deeply studied: identifying the target handle through image preprocessing and template matching technology， recovering the pose information between binocular cameras by feature detection and matching algorithm， and correcting the pose information of binocular cameras. In order to overcome the influence of uneven illumination in stereoscopic matching， a stereoscopic matching algorithm based on local fusion is proposed to obtain the disparity map. Finally， triangulation is used to calculate the depth information of the target handle in the train decomposition area to realize three-dimensional reconstruction. This method can measure the physical distance between the handles and the binocular vision system after identifying the position of the handles， so as to provide data basis for the automatic unhooking of the robot.