Object Detection and Text Recognition for Immersive Augmented Reality Training in Laser Powder Bed Fusion

Professional Training for laser powder bed fusion equipment operation typically is time consuming and expensive for end-users in metal Additive Manufacturing (AM). This study proposes a practical solution by leveraging Hyperskill software to develop a immersive training program compatible with Augme...

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Published in:Procedia computer science Vol. 232; pp. 913 - 923
Main Authors: Zhang, Hongji, Jiao, Yecheng, Yuan, Yizhuo, Li, Yuanchen, Wang, Yiqin, Lu, Wenfeng, Fuh, Jerry, Li, Bingbing
Format: Journal Article
Language:English
Published: Elsevier B.V 2024
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ISSN:1877-0509, 1877-0509
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Abstract Professional Training for laser powder bed fusion equipment operation typically is time consuming and expensive for end-users in metal Additive Manufacturing (AM). This study proposes a practical solution by leveraging Hyperskill software to develop a immersive training program compatible with Augmented Reality (AR) devices. The program incorporates the YOLOv7 object detection algorithm and the CRAFT(Character Region Awareness for Text detection) Four-stage text recognition algorithm, seamlessly bridging the gap between reality and simulation. Through a human subjects study, we demonstrate the effectiveness and viability of the AR program, showcasing its capacity to deliver real-time, comprehensive training in metal AM processes. This approach offers a balanced and efficient solution for improving professional training in the field of metal AM.
AbstractList Professional Training for laser powder bed fusion equipment operation typically is time consuming and expensive for end-users in metal Additive Manufacturing (AM). This study proposes a practical solution by leveraging Hyperskill software to develop a immersive training program compatible with Augmented Reality (AR) devices. The program incorporates the YOLOv7 object detection algorithm and the CRAFT(Character Region Awareness for Text detection) Four-stage text recognition algorithm, seamlessly bridging the gap between reality and simulation. Through a human subjects study, we demonstrate the effectiveness and viability of the AR program, showcasing its capacity to deliver real-time, comprehensive training in metal AM processes. This approach offers a balanced and efficient solution for improving professional training in the field of metal AM.
Author Jiao, Yecheng
Li, Bingbing
Li, Yuanchen
Fuh, Jerry
Yuan, Yizhuo
Zhang, Hongji
Wang, Yiqin
Lu, Wenfeng
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Keywords Object Detection
Immersive Augmented Reality Training
Text Recognition
Metal Additive Manufacturing
Language English
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SubjectTerms Immersive Augmented Reality Training
Metal Additive Manufacturing
Object Detection
Text Recognition
Title Object Detection and Text Recognition for Immersive Augmented Reality Training in Laser Powder Bed Fusion
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