发表机构
TH Köln - University of Applied Sciences（科隆应用技术大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出一种结合摄影测量与语义分割的视觉管道，用于机器人后处理中焊缝的近似定位，以减少大型工件扫描工作量与无关数据，为后续高精度测量做准备。
AI 中文摘要
准确识别焊缝几何形状对于打磨、精加工和检测等自动化机器人后处理操作至关重要。对于大型工件，使用高精度激光扫描仪或结构光传感器进行完整表面扫描可能非常耗时，且常产生大量无关数据。本文提出一种基于视觉的实验性管道，用于焊缝的近似定位，作为高精度测量前的初步阶段，旨在减少整体扫描工作量并提升数据采集效率。该方法包括从多个视点拍摄工件图像、通过语义分割从图像中识别焊缝、利用摄影测量重建工件，以及将识别出的焊缝投影到重建模型中。
英文摘要
Accurate identification of weld seam geometries is essential for automated robotic post processing operations such as grinding, finishing, and inspection. For large workpieces, complete surface scanning using high precision laser scanners or structured light sensors can be time consuming and often generates substantial amount of data that are not relevant. This paper presents an experimental vision based pipeline for the approximate localization of weld seams. This serves as a preliminary stage before high precision measurement. The proposed approach aims to reduce the overall scanning effort and data acquisition efficiency. The proposed method includes capturing images of the workpiece from multiple viewpoints, identifying weld seams from the images using semantic segmentation, reconstructing the workpiece using photogrammetry, and projection of identified weld seams into the reconstructed model.
CommentsExtended abstract not yet published to a conference or journal
