Unmanned Ground Vehicle and Robotic Arm Integration for Automated Welding

Doyun Lee, Georgia Southern University
Kevin Han, North Carolina State University

Publisher Copyright: © 2024 ASCE.

Abstract

Construction projects extensively use steel. Welding safety and quality concerns are vital since they are mainly used as structural components. By 2027, the welding industry will be short of 360,000 welders, despite its importance. The labor shortage and the need for consistent and efficient welding are strong drivers for developing an automated welding system. This paper presents the development of a mobile robotic welding system by integrating an unmanned ground vehicle (UGV) with visual sensors, a robotic arm, and a welding machine. This integrated robot can navigate to the welding location while avoiding a collision. It can detect welding joints automatically using a camera through deep learning algorithms. The robotic arm can move along the joint while scanning the joint in 3D using a line-laser scanner. Finally, it can perform welding along the 3D joint captured by the laser scanner. The results show that the integrated robot can reach the goal position within the margin of error and demonstrate the consistency and accuracy of welding.