Abstract
The use of automatic welding robots has become an important trend in the industry. Applying this technology not only helps increase production efficiency but also reduces risks and labor costs. In this context, our study proposes an advanced method by incorporating the YOLOv8 deep learning network into an automatic welding robot. The task of the YOLOv8 model is to detect and monitor welds in real time through a camera system. This helps automate the welding process by providing information about the position and shape of the weld points. Welding coordinate values are transmitted and the welding tip is adjusted to target specific welding points, creating an efficient and precise automated welding process. The paper also hopes that this research will encourage the development and application of artificial intelligence (AI) in the field of welding. By combining welding technology and artificial intelligence, it is believed that the welding industry will continue to progress and modernize while contributing to the sustainable development of global manufacturing.
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References
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