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- Title
Recent developments in computer vision and artificial intelligence aided intelligent robotic welding applications.
- Authors
Eren, Berkay; Demir, Mehmet Hakan; Mistikoglu, Selcuk
- Abstract
The welding process, which is an indispensable part of the manufacturing industry, has been in demand for years and continues to attract the attention of researchers. With the transition to Industry 4.0, the welding process got out of the control of the operators and became automated with sensors and artificial intelligence methods, and as a result, it became inevitable for industrial manipulators or robots to enter the production sector. One of the most important details in making the welding process autonomous in manufacturing is the sensors, and among the sensors are the vision sensors. In recent years, it is seen that robotic welding applications are applied very sensitively and successfully when visual sense and artificial intelligence are used together. This study comprehensively reviewed research and development for cutting-edge applications using visual sensors and artificial intelligence for robotic welding applications. The processes that are the subject of intelligent robotic welding applications such as calibration, determination of welding starting point, seam tracking, and welding quality are determined and discussed based on current studies and critical analyzes. The detection, tracking, diagnosis, classification, and prediction performances of various methods of machine learning (ML), which is one of the most used areas in artificial intelligence-based applications, in welding applications are examined comparatively. This review article will help researchers about what should be considered in vision sensor aided robotic welding applications and how to contribute more to studies with artificial intelligence support.
- Subjects
ROBOTIC welding; ARTIFICIAL intelligence; ARTIFICIAL vision; MANUFACTURING processes; IMAGE sensors; COMPUTER vision
- Publication
International Journal of Advanced Manufacturing Technology, 2023, Vol 126, Issue 11/12, p4763
- ISSN
0268-3768
- Publication type
Article
- DOI
10.1007/s00170-023-11456-4