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Silva, Jorge
Publications (1 of 1) Show all publications
Liu, Z., Silva, J., Zhong, R., Qin, Q., Roy, N., Nan Fernandez-Ayala, V., . . . Wang, L. (2026). ConstrucTwin: Digital Twin-Driven Multirobot Construction System Toward Industry 5.0. IEEE Transactions on Systems, Man & Cybernetics. Systems, 56(4), 2924-2939
Open this publication in new window or tab >>ConstrucTwin: Digital Twin-Driven Multirobot Construction System Toward Industry 5.0
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2026 (English)In: IEEE Transactions on Systems, Man & Cybernetics. Systems, ISSN 2168-2216, E-ISSN 2168-2232, Vol. 56, no 4, p. 2924-2939Article in journal (Refereed) Published
Abstract [en]

Rapid advancements in digitalization and artificial intelligence (AI) have catalyzed the adoption of digital twin technologies in the construction sector, enabling real-time synchronization between virtual models and physical systems. Simultaneously, on-site robotic automation has shown promise for reducing physical workloads, enhancing productivity, and contributing to sustainability goals that are key values of Industry 5.0. However, current digital twin implementations rarely incorporate multirobot construction systems, often relying on single-robot approaches or purely offline simulations. This gap hinders the realization of truly integrated construction environments that combine sensing, data analytics, wireless communications, and multirobot coordination. In response, this article proposes ConstrucTwin, a digital twin-driven multirobot construction framework designed to support complex construction tasks in real-world settings. By combining a 5G communication estimation-involved architecture and a cross-level planning strategy, ConstrucTwin streamlines interactions between physical robots and their digital counterparts. Essential tasks such as motion and task-level planning, as well as remote human-in-the-loop (HIL) oversight, are orchestrated within a single unified architecture. Through case studies involving rebar cage and brick wall construction, we demonstrate how an integrated approach to vision-based servoing and multirobot coordination enhances execution speed, precision, and scalability. The results underscore the system’s potential to advance human-centric, resilient, and sustainable construction, thereby aligning with the broader vision of Industry 5.0.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2026
Keywords
Digital twin, Industry 5.0, multirobot construction, smart construction
National Category
Construction Management Computer Sciences Robotics and automation
Identifiers
urn:nbn:se:kth:diva-377918 (URN)10.1109/TSMC.2026.3658622 (DOI)001696642500001 ()2-s2.0-105030692936 (Scopus ID)
Note

QC 20260320

Available from: 2026-03-11 Created: 2026-03-11 Last updated: 2026-03-20Bibliographically approved
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