基于双目视觉的载煤火车厢动态识别与定位  

Dynamic recognition and positioning of coal-carrying railway carriages based on binocular vision

作　　者：同志学[1] 陈佳杰 康智强[1] 屈东东 TONG Zhixue;CHEN Jiajie;KANG Zhiqiang;QU Dongdong(School of Mechanical and Electrical Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China)

机构地区：[1]西安建筑科技大学机电工程学院,陕西西安710055

出　　处：《Journal of Measurement Science and Instrumentation》2023年第2期148-155,共8页测试科学与仪器（英文版）

基　　金：Natural Science Foundation of Shaanxi Province(No.2019JM-286);Natural Scienceof Shaanxi Provincial Department of Education(No.17JK0445)。

摘　　要：载煤火车厢定位是煤炭采样机器人实现自主采样的关键技术之一。针对载煤火车厢的动态识别与定位问题,本文提出了一种双目立体视觉与改进YOLOv4-tiny结合的快速定位方法。该方法将双目相机左视图RGB图像作为改进YOLOv4-tiny的输入,得到载煤车厢在图像中的位置信息,再结合双目定位原理计算出其空间位置。改进后的算法主要对YOLOv4-tiny进行轻量化设计,采用了新的激活函数,并利用K-mans聚类算法重新生成样本先验锚框。与原网络相比,模型大小减少了62.5%,准确率提高了0.92%,召回率提高了0.89%,检测速度提高了20%。载煤火车厢在10 m以内的平均定位误差为4.1%,最大误差为8.3%。改进后的模型具有鲁棒性强、识别速度快、轻量化等优点,能够实现载煤火车厢的动态识别及定位,为煤炭采样机器人的自主采样提供了保证。The positioning of coal-carrying railway carriages is a critical technology for coal sampling robots to achieve autonomous sampling.A rapid positioning method for coal-carrying railway carriages combining binocular stereo vision and improved YOLOv4-tiny is proposed.The left view RGB image of the binocular camera is taken as the input of the improved YOLOv4-tiny.The position information of the coal-carrying railway car in the image is obtained.And its spatial distribution position is calculated based on the binocular positioning principle.The improved algorithm carries out a lightweight design for YOLOv4-tiny,adopts a new activation function,and uses the K-mans clustering algorithm to regenerate the prior anchor box.Compared with the original network,the model size has been reduced by 62.5%,the accuracy rate has been increased by 0.92%,the recall rate has been increased by 0.89%,and the detection speed has been increased by 20%.The average positioning error of the coal-carrying car within 10 m is 4.1%,and the maximum error is 8.3%.The improved model has the advantages of robustness,fast recognition speed,lightweight,etc.,and can realize the dynamic recognition of the coal-carrying car.The positioning provides a guarantee for the autonomous sampling of coal sampling robots.

关 键 词：载煤火车厢定位 深度学习 双目视觉 目标检测 YOLOv4-tiny 

分 类 号：U294.88[交通运输工程—交通运输规划与管理] TP391.41[交通运输工程—道路与铁道工程]