Path Planning with Automatic Seam Extraction over Point Cloud Models for Robotic Arc Welding

TL;DR

This paper introduces a robotic arc welding system that uses point cloud data, advanced filtering, and a novel seam extraction algorithm to automatically plan welding paths with high robustness and efficiency.

Contribution

The paper presents a new integrated system combining point cloud reconstruction, denoising, and a novel intensity-based seam extraction algorithm for automatic welding path planning.

Findings

System effectively reconstructs 3D models from partial scans.

The seam extraction algorithm accurately detects welding edges.

Experimental results show high robustness and efficiency in diverse scenarios.

Abstract

This paper presents a point cloud based robotic system for arc welding. Using hand gesture controls, the system scans partial point cloud views of workpiece and reconstructs them into a complete 3D model by a linear iterative closest point algorithm. Then, a bilateral filter is extended to denoise the workpiece model and preserve important geometrical information. To extract the welding seam from the model, a novel intensity-based algorithm is proposed that detects edge points and generates a smooth 6-DOF welding path. The methods are tested on multiple workpieces with different joint types and poses. Experimental results prove the robustness and efficiency of this robotic system on automatic path planning for welding applications.