Advancements in control systems and integration of artificial intelligence in welding robots: A review

Welding automation has witnessed significant advancements with the integration of control systems and artificial intelligence (AI) in welding robots. This review paper explores the significance of control systems in various welding methods, including arc, laser, spot, and friction stir welding. It highlights their role in achieving precise, efficient weld quality, reducing human errors, and executing complex tasks with high accuracy and repeatability. Sensor technologies play a crucial role in control systems, enabling real-time monitoring of welding parameters and ensuring optimal process control. Thus, various sensor technologies utilized in welding robots are examined, such as vision systems, force sensors, and temperature sensors, emphasizing their contribution to enhancing weld quality and overall system performance. Additionally, the application of welding robots in challenging environments, such as ocean pipeline welding, is discussed, highlighting the importance of robust control systems and sensor technologies in these contexts. Lastly, the paper delves into applying machine learning methods to welding robots, enabling the development of intelligent systems capable of adapting and optimizing the welding processes. The utilization of machine learning algorithms for weld defect detection, process parameter optimization, and predictive maintenance is discussed, representing the potential of integrating AI in welding robots to enhance their performance and efficiency. • Study of the significance of control systems in various welding methods. • Review and comparison of different control systems applied in Welding Robots. • Review of application and limitations of various Sensors used in welding robots. • Review of the state-of-the-art artificial intelligence use in Welding Robots.