Digital twin-enabled human-robot collaborative teaming towards sustainable and healthy built environments
Journal article
Lu, W.,, Chen, J., Fu, Y., Pan, Y. and Ghansah, F. (2023). Digital twin-enabled human-robot collaborative teaming towards sustainable and healthy built environments. Journal of Cleaner Production. 412, p. 137412. https://doi.org/10.1016/j.jclepro.2023.137412
Authors | Lu, W.,, Chen, J., Fu, Y., Pan, Y. and Ghansah, F. |
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Abstract | Development of sustainable and healthy built environments (SHBE) is highly advocated to achieve collective societal good. Part of the pathway to SHBE is the engagement of robots to manage the ever-complex facilities for tasks such as inspection and disinfection. However, despite the increasing advancements of robot intelligence, it is still “mission impossible” for robots to independently undertake such open-ended problems as facility management, calling for a need to “team up” the robots with humans. Leveraging digital twin's ability to capture real-time data and inform decision-making via dynamic simulation, this study aims to develop a human-robot teaming framework for facility management to achieve sustainability and healthiness in the built environments. A digital twin-enabled prototype system is developed based on the framework. Case studies showed that the framework can safely and efficiently incorporate robotics into facility management tasks (e.g., patrolling, inspection, and cleaning) by allowing humans to plan, oversee, manage, and cooperate with the robot via the digital twin's bi-directional mechanism. The study lays out a high-level framework, under which purposeful efforts can be made to unlock digital twin's full potential in collaborating humans and robots in facility management towards SHBE. |
Keywords | Sustainability, Green building, Human–robot teaming, Human–robot interaction, Digital twin |
Year | 2023 |
Journal | Journal of Cleaner Production |
Journal citation | 412, p. 137412 |
Publisher | Elsevier |
ISSN | 1879-1786 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.jclepro.2023.137412 |
Publication dates | |
12 May 2023 | |
Publication process dates | |
Accepted | 05 May 2023 |
Deposited | 19 Jan 2024 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/95y2z
Download files
Accepted author manuscript
Lu2023_DT_enabled_HRT_for_FM (1).pdf | ||
License: CC BY 4.0 | ||
File access level: Open |
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