Recent developments in computer vision and artificial intelligence aided intelligent robotic welding applications

Eren, Berkay; Demir, Mehmet Hakan; Mıstıkoğlu, Selçuk

doi:10.1007/s00170-023-11456-4

Cited by 16 publications

(2 citation statements)

References 170 publications

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“…The development of robotic welding sensors has been rapid in recent years, and their application in various industries has become increasingly widespread [ 123 , 124 , 125 ]. These sensors are designed to detect and measure various parameters such as temperature, pressure, speed, and position, which are crucial for ensuring consistent and high-quality welds.…”

Section: Robotic Welding Sensors In Industrial Applicationsmentioning

confidence: 99%

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Wang,

Li,

2023

Sensors

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With the rapid development of vision sensing, artificial intelligence, and robotics technology, one of the challenges we face is installing more advanced vision sensors on welding robots to achieve intelligent welding manufacturing and obtain high-quality welding components. Depth perception is one of the bottlenecks in the development of welding sensors. This review provides an assessment of active and passive sensing methods for depth perception and classifies and elaborates on the depth perception mechanisms based on monocular vision, binocular vision, and multi-view vision. It explores the principles and means of using deep learning for depth perception in robotic welding processes. Further, the application of welding robot visual perception in different industrial scenarios is summarized. Finally, the problems and countermeasures of welding robot visual perception technology are analyzed, and developments for the future are proposed. This review has analyzed a total of 2662 articles and cited 152 as references. The potential future research topics are suggested to include deep learning for object detection and recognition, transfer deep learning for welding robot adaptation, developing multi-modal sensor fusion, integrating models and hardware, and performing a comprehensive requirement analysis and system evaluation in collaboration with welding experts to design a multi-modal sensor fusion architecture.

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Section: Robotic Welding Sensors In Industrial Applicationsmentioning

confidence: 99%

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Wang,

Li,

2023

Sensors

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“…Determining the welding trajectory autonomously and following the specified welding path are very important in reducing operator-related errors and increasing the welding quality. Studies such as monitoring and realizing the weld trajectory autonomously with welding robots, improving the weld images together with them, determining the quality of the welding externally by methods such as machine learning and deep learning take place on a very large scale in the literature [1,2]. However, when welding is desired using an autonomous system, it is inevitable to use sensors.…”

Section: Introductionmentioning

confidence: 99%

Welding Robot Design with Machine Learning Based Intelligent Vision System

Eren,

Demir,

Mistikoglu

2023

imiens

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The use of welding technologies in the manufacturing sector plays a very important role and increases its popularity thanks to developing technologies. Welding technologies are used in almost every field where production takes place, and the speed and efficiency of welding technologies have increased in these sectors in recent years. The fact that artificial intelligence techniques are at the forefront and the efficient use of these techniques together with sensors has led to development in welding technology. Thus, welding robots emerged with the support of robots with artificial intelligence techniques, and adaptive systems that can adapt to different types of workpieces working autonomously in the manufacturing sector are shaping the sector. Despite these developments, non-autonomous systems are still used today by teaching the welding points to the robots by the operators. Along with the concept robotic system to be designed and implemented within the scope of this study, it is planned to determine the welding trajectory autonomously with artificial intelligence techniques, and to perform the welding process by following the welding trajectory by the robot.

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A new approach for detection of weld joint by image segmentation with deep learning-based TransUNet

Eren,

Demir,

Mistikoglu

2024

Int J Adv Manuf Technol

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Recent developments in computer vision and artificial intelligence aided intelligent robotic welding applications

Cited by 16 publications

References 170 publications

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Welding Robot Design with Machine Learning Based Intelligent Vision System

A new approach for detection of weld joint by image segmentation with deep learning-based TransUNet

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