Using digital twins and artificial intelligence for the synchronization of physical and virtual collaborative robots

Lisovskyi, A.

Публікація:
Using digital twins and artificial intelligence for the synchronization of physical and virtual collaborative robots

dc.contributor.author	Lisovskyi, A.
dc.date.accessioned	2025-10-04T11:22:22Z
dc.date.available	2025-10-04T11:22:22Z
dc.date.issued	2025
dc.description.abstract	This study proposes an approach to synchronizing physical and virtual collaborative robots based on the concept of digital twins and artificial intelligence tools. The proposed mathematical models allow formalising the processes of reflecting the real state of robots in a digital environment and minimising synchronisation errors. Particular attention is paid to the use of prediction, data filtering, and reinforcement learning algorithms that ensure the adaptability and stability of the system. The paper analyses the advantages of direct, predictive, and hybrid synchronisation methods and evaluates their effectiveness in a multi-user environment. The use of artificial intelligence allows for an increase in the level of autonomy and safety of human-robot interaction. The results of the study demonstrate the promise of integrating digital twins into modern robotic systems and open up opportunities for creating scalable and flexible manufacturing solutions.
dc.identifier.citation	Lisovskyi A. Using digital twins and artificial intelligence for the synchronization of physical and virtual collaborative robots / A. Lisovskyi // Manufacturing & Mechatronic Systems 2025 : Thesises of Reports of IX-st International Conference, October 25-26, 2025. - Kharkiv, 2025. - P. 11-14.
dc.identifier.uri	https://openarchive.nure.ua/handle/document/32850
dc.language.iso	en_US
dc.subject	digital twin
dc.subject	collaborative robot
dc.subject	fuzzy logic
dc.subject	reinforcement learning
dc.subject	artificial intelligence
dc.title	Using digital twins and artificial intelligence for the synchronization of physical and virtual collaborative robots
dc.type	Thesis
dspace.entity.type	Publication