拼装管片时需先将管片运送到待拼装位置，然后再局部微调管片位置和姿态，使其与相邻管片对齐。为准确获取管片的待拼装位置和姿态，提出一种快速识别已拼环管片位姿并预测待拼环管片拼装位姿的方法。首先，用面结构光相机获取已拼环管片纵缝点云，并利用两阶段手眼标定方法将其转换至拼装机器人的基坐标系下； 然后，基于管片点云进行纵缝分割、环缝检测，推算已拼环管片坐标和姿态，并根据待拼环管片排版位置关系推导出待拼环所有管片的预拼装位置和姿态。为验证该算法的有效性，在现场搭建管片自动拼装试验平台，利用该平台开展管片自动拼装试验。试验结果表明： 1）设计的基于密度聚类和SVM（支持向量机）的纵缝分割方法可有效将点云按管片分块； 2）提出的管片拼装定位方法定位误差较小，3个方向的坐标误差均在12.3 mm内，满足工程中管片拼装粗定位要求，可为管片位置和姿态的精细调整提供较为可靠的初始位置。

When conducting segment assembly, the position and orientation of the segments should be adjusted to align with adjacent segments after transporting to the designated position. To accurately capture installation position and orientation of the segments,, the authors develop a method for rapid identification of the posture of installed segments and prediction of the posture of segments to be assembled. The method employs a structured-light camera to capture the longitudinal joint point cloud of installed segments and applies a two-stage hand-eye calibration to transform the point cloud into the assembly robot′s base coordinate system. Based on the segment point cloud, longitudinal joint segmentation and circumferential joint detection are performed to determine the posture of installed segments. Using the arrangement scheme of the segments to be assembled, their preliminary installation positions and orientations are derived. An on-site experimental platform for automated segment assembly is constructed, and assembly tests are conducted to validate the proposed algorithm. The results show that: (1) the developed longitudinal joint segmentation method, based on density clustering and a support vector machine, effectively extracts the midline of the longitudinal joint; and (2) the proposed positioning method achieves low errors, with coordinate deviations in all three directions within 12.3 mm, thereby meeting the requirements for coarse positioning in segment assembly. This method provides a reliable initial reference for subsequent fine adjustments of segment posture.