基于深度学习视觉和激光辅助的盾构管片自动拼装定位方法  

Automatic assembly positioning method of shield tunnel segments based on deep learning vision and laser assistance

作　　者：吴志洋 王双[1,2,3] 刘铁根[1,2,3] 靳党鹏[4] Wu Zhiyang;Wang Shuang;Liu Tiegen;Jin Dangpeng(School of Precision Instruments and Optoelectronics Engineering,Tianjin University,Tianjin 300072,China;Key Laboratory of Optoelectronics Information Technology,Ministry of Education,Tianjin University,Tianjin 300072,China;Tianjin Optical Fiber Sensing Engineering Center,Institute of Optical Fiber Sensing,Tianjin University,Tianjin 300072,China;Tian He Mechanical Equipment Manufacturing Co.Ltd,Changshu 215500,China)

机构地区：[1]天津大学精密仪器与光电子工程学院,天津300072 [2]教育部光电信息技术重点实验室,天津300072 [3]天津大学光纤传感研究所天津光纤传感工程中心,天津300072 [4]中交天和机械设备制造有限公司,江苏常熟215500

出　　处：《红外与激光工程》2022年第4期242-250,共9页Infrared and Laser Engineering

基　　金：国家重点研究发展计划(2018YFF01013200)。

摘　　要：隧道管片定位是实现盾构管片自动拼装的关键。文中提出了一种基于深度学习视觉和激光辅助相结合的盾构管片自动拼装定位方法,分别利用视觉系统和激光测距系统计算待拼装管片的平面位姿和深度位姿信息。其中,视觉系统基于特殊设计的双阶段卷积神经网络可以实现管片表面定位标志轮廓特征的有效提取,提取精度和识别率相比于现有算法具有明显的提高。实验表明所提出的盾构管片自动拼装定位方法能够满足盾构管片自动拼装定位需求。The positioning of tunnel segments is the key to realize the automatic assembly of shield segments.This paper proposed a method for automatic assembly and positioning of shield segments based on the combination of deep learning vision and laser assistance.The plane pose and depth pose information of the segments to be assembled were obtained by vision system and laser ranging system,respectively.The vision system based on the specially designed two-stage convolutional neural network could effectively extract the contour features of the segment surface positioning marks,and the extraction accuracy and recognition rate were significantly improved compared with existing algorithms.Experiments show that the proposed automatic assembly positioning method of shield segment can meet the requirements of automatic assembly and positioning of shield segment.

关 键 词：深度学习 管片定位 特征提取 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置]