Scholarlink

<p>This paper proposes an integrated autonomous robotic welding algorithm that combines a deep learning-based vision model with a 3D sensing system. The framework utilizes an AI model trained on 2D images to automatically detect and localize the welding region, which is then mapped onto the corresponding 3D point cloud data. To ensure precision, a convexity-based geometric analysis is performed to extract workpiece edges and evaluate the spatial relationship between these edges and their surrounding surfaces. This process enables accurate detection of gaps along the welding path and the generation of an optimized welding trajectory. The technical feasibility and practicality of the proposed method were experimentally validated using a 6-DoF robotic manipulator equipped with a 3D laser scanning system.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Introduction to robotic welding algorithm

  • 期刊论文

  • 发表日期：

    2026年6月21日

查看全文
  • Kangmin Noh,
  • Hyunhwan Jeong

摘要

This paper proposes an integrated autonomous robotic welding algorithm that combines a deep learning-based vision model with a 3D sensing system. The framework utilizes an AI model trained on 2D images to automatically detect and localize the welding region, which is then mapped onto the corresponding 3D point cloud data. To ensure precision, a convexity-based geometric analysis is performed to extract workpiece edges and evaluate the spatial relationship between these edges and their surrounding surfaces. This process enables accurate detection of gaps along the welding path and the generation of an optimized welding trajectory. The technical feasibility and practicality of the proposed method were experimentally validated using a 6-DoF robotic manipulator equipped with a 3D laser scanning system.