TY - GEN
T1 - MR-MultiTwin
T2 - 26th IEEE China Conference on System Simulation Technology and its Applications, CCSSTA 2025
AU - Liu, Cong
AU - Zhang, Xiaoning
AU - Liang, Xiaojun
AU - Luo, Weichao
AU - He, Zhenyu
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - As Industry 5.0 accelerates, real-time, multi-user collaboration with digital twins (DTs) becomes increasingly essential. However, current systems struggle with spatial synchro-nization, collaborative execution, and natural interaction at scale. We introduce MR-MultiTwin, a mixed reality (MR) platform that addresses these gaps through three key innovations: (1) a shared-anchor-based spatial mapping method for aligning multi-user locations within a unified coordinate system; (2) a role-based collaboration framework that synchronizes task states, user identities, and control rights in real time; and (3) AI-powered multimodal interaction, integrating gesture, gaze, and voice for seamless DT control. Built on an edge-cloud architecture, MR-MultiTwin has been validated in smart manufacturing and inspection scenarios, showing notable gains in coordination effi-ciency, interaction usability, and deployment feasibility-paving the way for scalable industrial MR systems.
AB - As Industry 5.0 accelerates, real-time, multi-user collaboration with digital twins (DTs) becomes increasingly essential. However, current systems struggle with spatial synchro-nization, collaborative execution, and natural interaction at scale. We introduce MR-MultiTwin, a mixed reality (MR) platform that addresses these gaps through three key innovations: (1) a shared-anchor-based spatial mapping method for aligning multi-user locations within a unified coordinate system; (2) a role-based collaboration framework that synchronizes task states, user identities, and control rights in real time; and (3) AI-powered multimodal interaction, integrating gesture, gaze, and voice for seamless DT control. Built on an edge-cloud architecture, MR-MultiTwin has been validated in smart manufacturing and inspection scenarios, showing notable gains in coordination effi-ciency, interaction usability, and deployment feasibility-paving the way for scalable industrial MR systems.
KW - Digital Twin
KW - Industrial XR
KW - Industry 5.0
KW - Mixed Reality
KW - Multi-User Collaboration
KW - Role-Based Interaction
UR - https://www.scopus.com/pages/publications/105016779378
U2 - 10.1109/IEEECONF65522.2025.11137033
DO - 10.1109/IEEECONF65522.2025.11137033
M3 - 会议稿件
AN - SCOPUS:105016779378
T3 - Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025
SP - 399
EP - 404
BT - Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 July 2025 through 13 July 2025
ER -