| Yazarlar (3) |
Dr. Öğr. Üyesi Senem TANBERK
Senem Tanberk, Türkiye |
Dilek Bilgin Tukel
Doğuş Üniversitesi, Türkiye |
|
Kadir Acar
Kale, Türkiye |
| Özet |
| In the context of Industry 4.0, digital twin technology has emerged with rapid advancements as a powerful tool for visualizing and analyzing industrial assets. This technology has attracted considerable interest from researchers across diverse domains such as manufacturing, security, transportation, and gaming. The metaverse has emerged as a significant enabler in these domains, facilitating the integration of various technologies to create virtual replicas of physical assets. The utilization of 3D character animation, often referred to as avatars, is crucial for implementing the metaverse. Traditionally, costly motion capture technologies are employed for creating a realistic avatar system. To meet the needs of this evolving landscape, we have developed a modular framework tailored for asset digital twins as a more affordable alternative. This framework offers flexibility for the independent customization of individual system components. To validate our approach, we employ the English peg solitaire game as a use case, generating a solution tree using the breadth-first search algorithm. The results encompass both qualitative and quantitative findings of a data-driven 3D animation system utilizing motion primitives. The presented methodologies and infrastructure are adaptable and modular, making them applicable to asset digital twins across diverse business contexts. This case study lays the groundwork for pilot applications and can be tailored for education, health, or Industry 4.0 material development. |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale |
| Dergi Adı | arXiv preprint arXiv:2407.18934 |
| Dergi Tarandığı Indeksler | |
| Makale Dili | İngilizce |
| Basım Tarihi | 07-2024 |
