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Isaac Sim: Revolutionizing VR Controller Precision for Micromanipulation using Time2Vec+Transformer Model
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- Title
- Isaac Sim: Revolutionizing VR Controller Precision for Micromanipulation using Time2Vec+Transformer Model
- DGIST Authors
- Obasi Yetunde Oluwatoyosi ; Cheol Song ; Daewon Seo
- Advisor
- 송철
- Co-Advisor(s)
- Daewon Seo
- Issued Date
- 2025
- Awarded Date
- 2025-08-01
- Type
- Thesis
- Description
- Virtual Reality, Microsurgery, Transformer, Isaac Sim.
- Table Of Contents
-
Contents
List of Figures ii
List of Tables iv
1 Introduction 1
1.1 Study Background 1
1.2 Related Studies 1
1.2.1 Implementations of Virtual Reality 1
1.2.2 Applications and Significance of VR 2
1.3 Study Objective 2
1.4 Application of Isaac Sim in this study 3
2 Deep Learning Technique 5
2.1 Deep learning Algorithms 5
2.1.1 Recurrent Neural Networks (RNNs) 5
2.1.2 Transformer model 8
3 System Implementation 13
3.1 Hardware System 13
3.2 Software System 13
3.3 Schematic System Overview 14
3.4 Model Training and Evaluation Process 15
3.5 Configuration for Training 16
4 Experiments and Results 20
4.1 Experiment 1: Real-World Experiment 20
4.1.1 Methodology 20
4.1.2 Results 20
4.2 Experiment 2: Simulated Environment in Isaac Sim 22
4.2.1 Methodology 22
4.2.2 Results 23
4.2.3 Comparison Between Real-World and Synthetic Data 24
4.3 Experiment 3: Human-Participant Study Experiment 25
4.3.1 Results 27
5 Discussion and Conclusion 30
6 Future works 31
REFERENCES 32
- URI
-
https://scholar.dgist.ac.kr/handle/20.500.11750/59843
http://dgist.dcollection.net/common/orgView/200000888279
- Degree
- Master
- Department
- Artificial Intelligence Major
- Publisher
- DGIST
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