A Comprehensive Framework for Integrating Robotics and Digital Twins in Façade Perforation
Abstract
In contemporary design practices, the conflict between initial design approaches and subsequent manufacturing and construction stages presents a notable challenge. To address this disparity, our study aims to establish a comprehensive digital design workflow, bridging these gaps. The authors introduce a conceptual framework that seamlessly integrates the imperatives of LEED with the realm of robotic manufacturing, specifically tailored for construction sites. The proposed methodology encompasses four distinct iFOBOT modules: iFOBOT-environment, iFOBOT-design, iFOBOT-construct, and iFOBOT-monitor. The integration of these modules allows for a holistic approach to design and construction, fostering efficient collaboration between multidisciplinary teams. To validate the efficacy of the author’s approach, we conducted an empirical study involving the creation of a double-skin facade panel perforation using this integrated process. Initial findings emphasize the enhanced constructability achieved through simulated robotic interventions utilizing a heuristic function. Moreover, this research presents a functional prototype as a tangible embodiment of the method’s practical application and potential impact on the field of architectural design and construction.
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Abbasnejad, B., Nepal, M.P., Ahankoob, A., Nasirian, A., and Drogemuller, R., 2021. Building Information Modelling (BIM) adoption and implementation enablers in AEC firms: A systematic literature review. Architectural Engineering and Design Management, 17, pp.411-433. DOI: https://doi.org/10.1080/17452007.2020.1793721
Ali, A.K., Lee, O.J., and Park, C., 2020a. Near real-time monitoring of construction progress: Integration of extended reality and kinect V2. In: Proceedings of the International Symposium on Automation and Robotics in Construction. IAARC Publications, pp.24-31. DOI: https://doi.org/10.22260/ISARC2020/0005
Ali, A.K., Lee, O.J., and Song, H., 2020b. Generic design aided robotically facade pick and place in construction site dataset. Data in Brief, 31, p.105933. DOI: https://doi.org/10.1016/j.dib.2020.105933
Ali, A.K., Lee, O.J., and Song, H., 2021. Robot-based facade spatial assembly optimization. Journal of Building Engineering, 33, p.101556. DOI: https://doi.org/10.1016/j.jobe.2020.101556
Babatunde, S.O., Ekundayo, D., Adekunle, A.O., and Bello, W., 2020. Comparative analysis of drivers to BIM adoption among AEC firms in developing countries: A case of Nigeria. Journal of Engineering Design and Technology, 18, pp.1425-1447. DOI: https://doi.org/10.1108/JEDT-08-2019-0217
Bosché, F., Guillemet, A., Turkan, Y., Haas, C.T., and Haas, R., 2014. Tracking the built status of MEP works: Assessing the value of a Scan-vs-BIM system. Journal of Computing in Civil Engineering, 28, p.05014004. DOI: https://doi.org/10.1061/(ASCE)CP.1943-5487.0000343
Caruso, L., Russo, R., and Savino, S., 2017. Microsoft Kinect V2 vision system in a manufacturing application. Robotics and Computer-Integrated Manufacturing, 48, pp.174-181. Fologram, 2018. Food4Rhino. Available from: https://www.food4rhino.com/en/app/fologram [Last accessed on 2023 Aug 14]. DOI: https://doi.org/10.1016/j.rcim.2017.04.001
Hashemi, M., 2021. Human-Robot Collaborative Design (HRCoD): Real-Time Collaborative Cyber-Physical HMI Platform for Robotic Design and Assembly through Augmented Reality (PhD Thesis). Kent State University.
Hook, J., 2016. Automated Digital Fabrication Concept for Composite Facades. Honours Thesis. The University of Queensland.
Jenny, S.E., Pietrasik, L.L., Sounigo, E., Tsai, P.H., Gramazio, F., Kohler, M., Lloret-Fritschi, E., and Hutter, M., 2023. Continuous mobile thin-layer on-site printing. Automation in Construction, 146, p.104634. DOI: https://doi.org/10.1016/j.autcon.2022.104634
Keating, S., and Oxman, N., 2013. Compound fabrication: A multi-functional robotic platform for digital design and fabrication. Robotics and Computer Integrated Manufacturing, 29, pp.439-448. DOI: https://doi.org/10.1016/j.rcim.2013.05.001
Keating, S.J., Leland, J.C., Cai, L., and Oxman, N., 2017. Toward site-specific and self-sufficient robotic fabrication on architectural scales. Science Robotics, 2, p.eaam8986. DOI: https://doi.org/10.1126/scirobotics.aam8986
Kim, M., Konstantzos, I., and Tzempelikos, A., 2020. Real-time daylight glare control using a low-cost, window-mounted HDRI sensor. Building and Environment, 177, p.106912. DOI: https://doi.org/10.1016/j.buildenv.2020.106912
Kim, Y.S., Jung, M.H., Cho, Y.K., Lee, J., and Jung, U., 2007. Conceptual design and feasibility analyses of a robotic system for automated exterior wall painting. International Journal of Advanced Robotic Systems, 4, p.49. DOI: https://doi.org/10.5772/5668
Kontovourkis, O., Tryfonos, G., and Georgiou, C., 2020. Robotic additive manufacturing (RAM) with clay using topology optimization principles for toolpath planning: The example of a building element. Architectural Science Review, 63, pp.105-118. DOI: https://doi.org/10.1080/00038628.2019.1620170
Krieg, O.D., 2022. Architectural Potentials of Robotic Manufacturing in Timber Construction: Strategies for Interdisciplinary Innovation in Manufacturing and Design. Institute for Computational Design and Construction, University, Stuttgart.
KUKA. Prc- Parametric Robot Control for Grasshopper, 2011. Food4Rhino. Available from: https://www.food4rhino.com/en/app/kukaprc-parametric-robot control-grasshopper [Last accessed on 2023 Aug 14].
Kurtser, P., Ringdahl, O., Rotstein, N., Berenstein, R., and Edan, Y., 2020. In-field grape cluster size assessment for vine yield estimation using a mobile robot and a consumer level RGB-D camera. IEEE Robotics and Automation Letters, 5, pp.2031-2038. DOI: https://doi.org/10.1109/LRA.2020.2970654
Kwon, O.S., Park, C.S., and Lim, C.R., 2014. A defect management system for reinforced concrete work utilizing BIM, image-matching and augmented reality. Automation in Construction, 46, pp.74-81. DOI: https://doi.org/10.1016/j.autcon.2014.05.005
Park, C.S., Lee, D.Y., Kwon, O.S., and Wang, X., 2013. A framework for proactive construction defect management using BIM, augmented reality and ontology-based data collection template. Automation in Construction, 33, pp.61-71. DOI: https://doi.org/10.1016/j.autcon.2012.09.010
Rahimian, F.P., Seyedzadeh, S., Oliver, S., Rodriguez, S., and Dawood, N., 2020. On-demand monitoring of construction projects through a game-like hybrid application of BIM and machine learning. Automation in Construction, 110, p.103012. DOI: https://doi.org/10.1016/j.autcon.2019.103012
Rea, P., and Ottaviano, E., 2018. Design and development of an inspection robotic system for indoor applications. Robotics and Computer-Integrated Manufacturing, 49, pp.143-151. DOI: https://doi.org/10.1016/j.rcim.2017.06.005
Rebolj, D., Pučko, Z., Babič, N.Č., Bizjak, M., and Mongus, D., 2017. Point cloud quality requirements for Scan-vs-BIM based automated construction progress monitoring. Automation in Construction, 84, pp.323-334. DOI: https://doi.org/10.1016/j.autcon.2017.09.021
Weerasinghe, I.T., Ruwanpura, J.Y., Boyd, J.E., and Habib, A.F., 2012. Application of Microsoft Kinect sensor for tracking construction workers. In: Construction Research Congress 2012: Construction Challenges in a Flat World. American Society of Civil Engineers, Reston, pp.858-867. DOI: https://doi.org/10.1061/9780784412329.087
Willmann, J., Knauss, M., Bonwetsch, T., Apolinarska, A.A., Gramazio, F., and Kohler, M., 2016. Robotic timber construction-Expanding additive fabrication to new dimensions. Automation in Construction, 61, pp.16-23. DOI: https://doi.org/10.1016/j.autcon.2015.09.011
Yang, D., Li, Y., Li, T., Zhang, T., Han, M., and Yan, H., 2020. The system design of external cladding installation robot. International Journal of Advanced Robotic Systems, 17. ZED 2 - AI Stereo Camera, n.d. Stereolabs. Available from: https://www.stereolabs.com/zed-2 [Last accessed on 2023 Aug 14]. DOI: https://doi.org/10.1177/1729881420969062
Zied, K., 2007. An augmented framework for practical development of construction robots. International Journal of Advanced Robotic Systems, 4, p.43 DOI: https://doi.org/10.5772/5675
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