AR/VR Digital Twin for simulation and data collection of robotic environments

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2025

Autores

Marcelo Petry (Autor) FEUP; Martins, JG (Autor) Outra; Nutonen, K (Autor) Outra; Costa, P (Autor) Outra; Kuts, V (Autor) Outra; Otto, T (Autor) Outra; Armando Jorge Sousa (Autor) FEUP

Ata de Conferência Internacional

Título: 2025 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Páginas: 198-203

2025 International Conference on Autonomous Robot Systems and Competitions-ICARSC-Annual

Funchal, PORTUGAL, APR 02-03, 2025

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-018-NVS

DOI: 10.1109/icarsc65809.2025.10970158

Abstract (EN): Digital twins enable real-time modeling, simulation, and monitoring of complex systems, driving advancements in automation, robotics, and industrial applications. This study presents a large-scale digital twin-testing facility for evaluating mobile robots and pilot robotic systems in a research laboratory environment. The platform integrates high-fidelity physical and environmental models, providing a controlled yet dynamic setting for analyzing robotic behavior. A key feature of the system is its comprehensive data collection framework, capturing critical parameters such as position, orientation, and velocity, which can be leveraged for machine learning, performance optimization, and decision-making. The facility also supports the simulation of discrete operational systems, using predictive modeling to bridge informational gaps when real-time data updates are unavailable. The digital twin was validated through a matrix manufacturing system simulation, with an Augmented Reality (AR) interface on the HoloLens 2 to overlay digital information onto mobile platform controllers, enhancing situational awareness. The main contributions include a digital twin framework for deploying data-driven robotic systems and three key AR/VR integration optimization methods. Demonstrated in a laboratory setting, the system is a versatile tool for research and industrial applications, fostering insights into robotic automation and digital twin scalability while reducing costs and risks associated with real-world testing.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6