Enhancing augmented reality with machine learning for hands-on origami training
This research explores integrating augmented reality (AR) with machine learning (ML) to enhance hands-on skill acquisition through origami folding. We developed an AR system using the YOLOv8 model to provide real-time feedback and automatic validation of each folding step, offering step-by-step guid...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
|
| Series: | Frontiers in Virtual Reality |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frvir.2025.1499830/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832585014299066368 |
|---|---|
| author | Mikołaj Łysakowski Jakub Gapsa Chenxu Lyu Thomas Bohné Sławomir Konrad Tadeja Piotr Skrzypczyński Piotr Skrzypczyński |
| author_facet | Mikołaj Łysakowski Jakub Gapsa Chenxu Lyu Thomas Bohné Sławomir Konrad Tadeja Piotr Skrzypczyński Piotr Skrzypczyński |
| author_sort | Mikołaj Łysakowski |
| collection | DOAJ |
| description | This research explores integrating augmented reality (AR) with machine learning (ML) to enhance hands-on skill acquisition through origami folding. We developed an AR system using the YOLOv8 model to provide real-time feedback and automatic validation of each folding step, offering step-by-step guidance to users. A novel approach to training dataset preparation was introduced, which improves the accuracy of detecting and assessing origami folding stages. In a formative user study involving 16 participants tasked with folding multiple origami models, the results revealed that while the ML-driven feedback increased task completion times, it also made participants feel more confident throughout the folding process. However, they also reported that the feedback system added cognitive load, slowing their progress, though it provided valuable guidance. These findings suggest that while ML-supported AR systems can enhance the user experience, further optimization is required to streamline the feedback process and improve efficiency in complex manual tasks. |
| format | Article |
| id | doaj-art-a3123653dece4af9ae62bf4173ceb9d5 |
| institution | Kabale University |
| issn | 2673-4192 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Virtual Reality |
| spelling | doaj-art-a3123653dece4af9ae62bf4173ceb9d52025-01-27T06:40:31ZengFrontiers Media S.A.Frontiers in Virtual Reality2673-41922025-01-01610.3389/frvir.2025.14998301499830Enhancing augmented reality with machine learning for hands-on origami trainingMikołaj Łysakowski0Jakub Gapsa1Chenxu Lyu2Thomas Bohné3Sławomir Konrad Tadeja4Piotr Skrzypczyński5Piotr Skrzypczyński6Center for Artificial Intelligence and Cybersecurity, Poznań University of Technology, Poznań, PolandFaculty of Mechanical Engineering, Poznań University of Technology, Poznań, PolandDepartment of Engineering, University of Cambridge, Cambridge, United KingdomDepartment of Engineering, University of Cambridge, Cambridge, United KingdomDepartment of Engineering, University of Cambridge, Cambridge, United KingdomCenter for Artificial Intelligence and Cybersecurity, Poznań University of Technology, Poznań, PolandInstitute of Robotics and Machine Intelligence, Poznań University of Technology, Poznań, PolandThis research explores integrating augmented reality (AR) with machine learning (ML) to enhance hands-on skill acquisition through origami folding. We developed an AR system using the YOLOv8 model to provide real-time feedback and automatic validation of each folding step, offering step-by-step guidance to users. A novel approach to training dataset preparation was introduced, which improves the accuracy of detecting and assessing origami folding stages. In a formative user study involving 16 participants tasked with folding multiple origami models, the results revealed that while the ML-driven feedback increased task completion times, it also made participants feel more confident throughout the folding process. However, they also reported that the feedback system added cognitive load, slowing their progress, though it provided valuable guidance. These findings suggest that while ML-supported AR systems can enhance the user experience, further optimization is required to streamline the feedback process and improve efficiency in complex manual tasks.https://www.frontiersin.org/articles/10.3389/frvir.2025.1499830/fullaugmented realitymachine learningedge computingassembly taskeducation |
| spellingShingle | Mikołaj Łysakowski Jakub Gapsa Chenxu Lyu Thomas Bohné Sławomir Konrad Tadeja Piotr Skrzypczyński Piotr Skrzypczyński Enhancing augmented reality with machine learning for hands-on origami training Frontiers in Virtual Reality augmented reality machine learning edge computing assembly task education |
| title | Enhancing augmented reality with machine learning for hands-on origami training |
| title_full | Enhancing augmented reality with machine learning for hands-on origami training |
| title_fullStr | Enhancing augmented reality with machine learning for hands-on origami training |
| title_full_unstemmed | Enhancing augmented reality with machine learning for hands-on origami training |
| title_short | Enhancing augmented reality with machine learning for hands-on origami training |
| title_sort | enhancing augmented reality with machine learning for hands on origami training |
| topic | augmented reality machine learning edge computing assembly task education |
| url | https://www.frontiersin.org/articles/10.3389/frvir.2025.1499830/full |
| work_keys_str_mv | AT mikołajłysakowski enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining AT jakubgapsa enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining AT chenxulyu enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining AT thomasbohne enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining AT sławomirkonradtadeja enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining AT piotrskrzypczynski enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining AT piotrskrzypczynski enhancingaugmentedrealitywithmachinelearningforhandsonorigamitraining |