吴志洋, 王双, 刘铁根, 靳党鹏. 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[J]. 红外与激光工程, 2022, 51(4): 20210183. DOI: 10.3788/IRLA20210183
引用本文: 吴志洋, 王双, 刘铁根, 靳党鹏. 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[J]. 红外与激光工程, 2022, 51(4): 20210183. DOI: 10.3788/IRLA20210183
Wu Zhiyang, Wang Shuang, Liu Tiegen, Jin Dangpeng. Automatic assembly positioning method of shield tunnel segments based on deep learning vision and laser assistance[J]. Infrared and Laser Engineering, 2022, 51(4): 20210183. DOI: 10.3788/IRLA20210183
Citation: Wu Zhiyang, Wang Shuang, Liu Tiegen, Jin Dangpeng. Automatic assembly positioning method of shield tunnel segments based on deep learning vision and laser assistance[J]. Infrared and Laser Engineering, 2022, 51(4): 20210183. DOI: 10.3788/IRLA20210183

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

  • 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。

     

    Abstract: 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.

     

/

返回文章
返回