Robotic welding is an essential technology in industrial production. Various sensors are integrated into robotic welding systems to enhance welding efficiency and quality. Due to their advantages of non-contact measurement, high information capacity, and high accuracy, vision sensors play an increasingly important role in robotic autonomous welding. Therefore, the latest vision-based autonomous robotic arc welding technologies are comprehensively summarized, providing valuable reference and support for researchers. First, the research progress of visual sensing technology for welding robots is outlined, and its advantages and disadvantages are analyzed. Subsequently, the key technologies of robotic autonomous welding are introduced, covering weld type identification, initial point guidance, welding path generation, welding parameter planning, feature point extraction, seam tracking, welding posture adjustment, and welding quality control. Finally, the limitations existing in current research are summarized, and the future research directions of autonomous robotic welding are prospected. Note to Practitioners—Most current programming methods for welding robots rely on manual teaching and offline programming, limiting their adaptability to small batches and diverse categories in production. With the development of artificial intelligence and deep learning, vision-based technologies are propelling welding robots toward greater intelligence and autonomy. Autonomous welding robot technology is continuously advancing in areas such as weld type identification, initial point guidance, welding path generation, welding parameter planning, feature point extraction, seam tracking, welding posture adjustment, and welding quality control. This paper systematically reviews relevant research to date and outlines the future development directions of autonomous robotic arc welding.
