Open root pass welding in Gas Metal Arc Welding (GMAW) is always challenging due to the nonlinear random variations in pipe gaps and the presence of tacks.Manual welding requires a lot of skill from senior welders to react and control many variables promptly.In the transition to robotic welding, tracking solutions based on laser or vision systems have emerged to address the tracking issue.However, adapting the welding parameters (e.g.wire feed speed) and motion parameters (e.g.travel speed) is still essential in getting a consistent, high-quality weld.This work presents an adaptive control approach to pipe welding.The method combines a visionbased system that replicates the perception of welders with real-time control to live-adjust welding and motion parameters based on the instantaneous pipe gap, learning about the tack and fusing it on the root pass -a critical challenge for robotic welding applications.The controller monitors the state condition and communicates the proper process and motion update with the robot according to the real-time gap and tack state.The resulting closed-loop system enables higher quality and consistency of weld throughout the pipe welding.
