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Automation and Robotics Technologies Deployment Trends in Construction

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Automation and Robotics in the Architecture, Engineering, and Construction Industry

Abstract

The construction industry has remained very much less digitized than similar mature industries, with a good number of its activities being laborious and monotonous. With the construction industry gradually entering the era of industrialization and digitization, there is an opportunity to increasingly change the traditional approach of designing, constructing, operating, and maintaining buildings and infrastructure. The era of technological disruption ushers in the penetration of innovative construction tools, including automation and robotics technologies, in the industry. In construction, automation and robotics processes involve the autonomous execution of tasks and processes through intelligent programming and control of machines. This chapter explores the current state of automation and robotics technologies deployment in the construction industry and discusses potential automation and robotics applications in different aspects of construction projects. Construction companies can use these technologies to benchmark their technology adoption efforts.

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References

  1. F. Barbosa, J. Woetzel, J. Mischke, M.J. Ribeirinho, M. Sridhar, N. Bertram, S. Brown, Reinventing Construction: A Route to Higher Productivity (McKinsey Global Institute, McKinsey & Company, 2017) https://www.mckinsey.com/business-functions/operations/our-insights/reinventing-construction-through-a-productivity-revolution. Accessed 10.03.17

    Google Scholar 

  2. S. Witthoeft, I. Kosta, Shaping the Future of Construction. Inspiring Innovators Redefine the Industry (World Economic Forum, 2017) http://www3.weforum.org/docs/WEF_Shaping_the_Future_of_Construction_Inspiring_Innovators_redefine_the_industry_2017.pdf. REF 020117. Accessed 12.04.18

    Google Scholar 

  3. United Nations, World Urbanization Prospects 2018, illustrated revised ed., United Nations Publications, UN, 2019. ISBN 9211483190, 9789211483192

    Google Scholar 

  4. J. Woetzel, N. Garemo, J. Mischke, P. Kamra, R. Palter, Bridging Infrastructure Gaps. Has the World Made Progress? (McKinsey Global Institute, McKinsey & Company, 2017) https://www.mckinsey.com/business-functions/operations/our-insights/bridging-infrastructure-gaps-has-the-world-made-progress. Accessed 13.01.18

    Google Scholar 

  5. Bureau of Labor Statistics, Integrated BLS-BEA Industry-Level Production Account Tables. https://www.bls.gov/mfp/indprod11.xlsx, 2018. Accessed 02.27.2021

  6. T. Bock, T. Linner, Robot-Oriented Design: Design and Management Tools for the Deployment of Automation and Robotics in Construction (Cambridge University Press, Cambridge, 2015). https://doi.org/10.1017/cbo9781139924146

    Book  Google Scholar 

  7. S.S. Kamaruddin, M.F. Mohammad, R. Mahbub, Barriers and impact of mechanisation and automation in construction to achieve better quality products. Procedia. Soc. Behav. Sci. 222, 111–120 (2016). https://doi.org/10.1016/j.sbspro.2016.05.197

    Article  Google Scholar 

  8. T. Linner, W. Pan, R. Hu, C. Zhao, K. Iturralde, M. Taghavi, J. Trummer, M. Schlandt, T. Bock, A technology management system for the development of single-task construction robots. Constr. Innov. 20, 96–111 (2020). https://doi.org/10.1108/CI-06-2019-0053

    Article  Google Scholar 

  9. R. Agarwal, S. Chandrasekaran, M. Sridhar, Imagining construction’s digital future (McKinsey Productivity Sciences Center, Singapore, McKinsey & Company, 2016) https://www.mckinsey.com/business-functions/operations/our-insights/imagining-constructions-digital-future. Accessed 15.08.19

    Google Scholar 

  10. T. Bock, The future of construction automation: Technological disruption and the upcoming ubiquity of robotics. Automat. Constr. 59, 113–121 (2015). https://doi.org/10.1016/j.autcon.2015.07.022

    Article  Google Scholar 

  11. Autodesk, Inc. 2018, Connected BIM for building design: Improved project insight with the cloud. https://www.autodesk.com/solutions/bim/discover-building-design/bim-for-building-design. Accessed 15.06.19

    Google Scholar 

  12. S. Duvernoy, Architecture’s new media: Principles, theories, and methods of computer-aided design. Nexus Netw. J. 7, 163–165 (2005). https://doi.org/10.1007/s00004-005-0015-1

    Article  Google Scholar 

  13. R. Sacks, C. Eastman, G. Lee, P. Teicholz, BIM Handbook A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors, and Facility Managers, 3rd edn. (Wiley, 2018) ISBN: 978-1-119-28753-7

    Book  Google Scholar 

  14. A. Krivonogov, G. Zakharova, S. Kruglikov, S. Plotnikov, Implementation of BIM-technologies in the educational program of the architectural university. MATEC Web Conf. 146, 01001 (2018). https://doi.org/10.1051/matecconf/201814601001

    Article  Google Scholar 

  15. K. Schwab, The fourth industrial revolution (industry 4.0) a social innovation perspective. Techn. Innov. Manag. Rev. 7, 12–20 (2017). https://doi.org/10.22215/timreview/1117

    Article  Google Scholar 

  16. T.D. Oesterreich, F. Teuteberg, Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry. Comput. Ind. 83, 121–139 (2016). https://doi.org/10.1016/j.compind.2016.09.006

    Article  Google Scholar 

  17. Merriam-Webster, Robot | Definition of Robot by Merriam-Webster (Merriam-Webster, 2018) https://www.merriam-webster.com/dictionary/robot. Accessed 10.10.18

    Google Scholar 

  18. R. Rennie, J. Law (eds.), A Dictionary of Physics, 8th edn. (Oxford University Press, 2019). https://doi.org/10.1093/acref/9780198821472.001.0001

    Book  Google Scholar 

  19. M. Hewitt, J. Gambatese, Automation Consideration During Project Design, in Proceedings of the 19th International Symposium on Automation and Robotics in Construction, (The International Association for Automation and Robotics in Construction, Washington, USA, 2002), pp. 197–203. https://doi.org/10.22260/isarc2002/0031

    Chapter  Google Scholar 

  20. S.M.S. Elattar, Automation and robotics in construction: Opportunities and challenges, Emirates. J. Eng. Res. 13, 21–26 (2008) http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.524.7909

    Google Scholar 

  21. A.N. Ruggiero, C.L.S. Laurent, S.D. Salvo, Robotics in Construction (Worcester Polytechnic Institute Digital WPI, 2016) https://digitalcommons.wpi.edu/iqp-all/2749?utm_source=digitalcommons.wpi.edu%2Fiqp-all%2F2749&utm_medium=PDF&utm_campaign=PDFCoverPages. Accessed 20.03.19

    Google Scholar 

  22. A. Kerr (ed.), Dictionary of World History, 3rd edn. (Oxford University Press, Oxford, 2015). https://doi.org/10.1093/acref/9780199685691.001.0001

    Book  Google Scholar 

  23. World Encyclopedia (Phillip’s, Oxford, 2014). https://doi.org/10.1093/acref/9780199546091.001.0001

  24. Merriam-Webster, Automation | Definition of Automation by Merriam-Webster (Merriam-Webster, 2018) https://www.merriam-webster.com/dictionary/automation. Accessed 10.10.18

    Google Scholar 

  25. J. Scott, G. Marshall, A Dictionary of Sociology, 3rd edn. (Oxford University Press, Oxford, 2009). https://doi.org/10.1093/acref/9780199533008.001.0001

    Book  Google Scholar 

  26. M. Rajgor, J. Pitroda, Automation: A new millennium technology for construction industries. Global Res. Anal. 9, 79–81 (2013) ISSN 2277-8160

    Google Scholar 

  27. C. Soanes, A. Stevenson (eds.), Concise Oxford English Dictionary, 11th edn. (Oxford University Press, Oxford, 2005) ISBN-10: 019861-475

    Google Scholar 

  28. Merriam-Webster, Construction | Definition of Construction by Merriam-Webster (Merriam-Webster, 2018) https://www.merriam-webster.com/dictionary/construction. Accessed 10.10.18

    Google Scholar 

  29. R.A. Buswell, R.C. Soar, A.G.F. Gibb, A. Thorpe, Freeform construction: Mega-scale rapid manufacturing for construction. Automat. Constr. 16, 224–231 (2007). https://doi.org/10.1016/j.autcon.2006.05.002

    Article  Google Scholar 

  30. T. Bock, T. Linner, Construction Robots: Elementary Technologies and Single-Task Construction Robots (Cambridge University Press, Cambridge, 2017). https://doi.org/10.1017/CBO9781139872041

    Book  Google Scholar 

  31. B. Jørgensen, S. Emmitt, Lost in transition: The transfer of lean manufacturing to construction. Eng. Const. Archit. Manage. 15, 383–398 (2008). https://doi.org/10.1108/09699980810886874

    Article  Google Scholar 

  32. L.D. Xu, E.L. Xu, L. Li, Industry 4.0: State of the art and future trends. Int. J. of Prod. Res. 56, 2941–2962 (2018). https://doi.org/10.1080/00207543.2018.1444806

    Article  Google Scholar 

  33. J.M. Beer, A.D. Fisk, W.A. Rogers, Toward a framework for levels of robot autonomy in human-robot interaction. J Hum Robot Interact. 3, 74–99 (2014). https://doi.org/10.5898/JHRI.3.2.Beer

    Article  Google Scholar 

  34. H. Shakhatreh, A.H. Sawalmeh, A. Al-Fuqaha, Z. Dou, E. Almaita, I. Khalil, N.S. Othman, A. Khreishah, M. Guizani, Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges. IEEE Access. 7, 48572–48634 (2019). https://doi.org/10.1109/ACCESS.2019.2909530

    Article  Google Scholar 

  35. R. Bogue, What are the prospects for robots in the construction industry? Ind. Rob. 45, 1–6 (2018). https://doi.org/10.1108/IR-11-2017-0194

    Article  Google Scholar 

  36. J. Chen, Y. Fang, Y.K. Cho, C. Kim, Principal axes descriptor for automated construction-equipment classification from point clouds. J. Comput. Civ. Eng. 31, 04016058 (2017). https://doi.org/10.1061/(asce)cp.1943-5487.0000628

    Article  Google Scholar 

  37. E. Fallon (ed.), A Look at 3D Laser Scanning in the Construction Industry and Beyond, The Expert Report: The Newsletter of the Duggan Rhodes Group (Pittsburg, PA, 2012)

    Google Scholar 

  38. T. Randall, Construction engineering requirements for integrating laser scanning technology and building information modeling. J. Constr. Eng. Manag. 137, 797–805 (2011). https://doi.org/10.1061/(asce)co.1943-7862.0000322

    Article  Google Scholar 

  39. S. Chiodini, R.G. Reid, B. Hockman, I.A.D. Nesnas, S. Debei, M. Pavone, Robust visual localization for hopping rovers on small bodies, in 2018 IEEE International Conference on Robotics and Automation, (Institute of Electrical and Electronics Engineers, Brisbane, QLD, Australia, 2019), pp. 897–903. https://doi.org/10.1109/ICRA.2018.8462865

    Chapter  Google Scholar 

  40. T. Narumi, S. Aoki, F. Muramatsu, Indoor Visualization Experiments at Building Construction Site Using High Safety UAV, in Proceedings of the 36th International Symposium on Automation and Robotics in Construction, (The International Association for Automation and Robotics in Construction, Banff, Canada, 2019), pp. 961–966. https://doi.org/10.22260/isarc2019/0128

    Chapter  Google Scholar 

  41. Doxel, Artificial intelligence for construction productivity (2020). https://www.doxel.ai. Accessed 10.09.19

    Google Scholar 

  42. R. Eiris, M. Gheisari, B. Esmaeili, PARS: Using augmented 360-degree panoramas of reality for construction safety training. Int. J. Environ. Res. Public Health 15, 2452 (2018). https://doi.org/10.3390/ijerph15112452

    Article  Google Scholar 

  43. N.J. Shih, J.T. Lai, Y.L. Tsai, The application of a panorama image database management systems (PIDMS) for information integration on construction sites. ITcon. 11, 641–654 (2006) https://www.itcon.org/2006/44

    Google Scholar 

  44. M. Gheisari, G. Williams, Using Augmented Panoramic Views as an Online Course Delivery Mechanism in MOOCs, in 51st ASC Annual International Conference Proceedings, (Associated Schools of Construction, College Station, TX, 2015) http://ascpro0.ascweb.org/archives/cd/2015/paper/CERT337002015.pdf

    Google Scholar 

  45. R. Eiris, H.I. Moud, M. Gheisari, Using 360-Degree interactive panoramas to develop virtual representation of construction sites, in Lean and Computing in Construction Congress, (ITC Digital Library, Heraklion, Greece, 2017), pp. 775–782. https://doi.org/10.24928/jc3-2017/0122

    Chapter  Google Scholar 

  46. H.C. Pham, N.N. Dao, A. Pedro, Q.T. Le, R. Hussain, S. Cho, C.S. Park, Virtual field trip for mobile construction safety education using 360-degree panoramic virtual reality. Int. J. Eng. Educ. 34, 1174–1191 (2018) https://www.ijee.ie/latestissues/Vol34-4/05_ijee3626.pdf

    Google Scholar 

  47. K. Kensek, D. Noble, M. Schiler, A. Tripathi, Augmented reality: An application for architecture, in Eighth International Conference on Computing in Civil and Building Engineering, (American Society of Civil Engineers, Stanford, CA, 2000), pp. 294–301. https://doi.org/10.1061/40513(279)38

    Chapter  Google Scholar 

  48. J. Fogarty, J. McCormick, S. El-Tawil, Improving student understanding of complex spatial arrangements with virtual reality. J. Prof. Issues in Eng. Educ. Pract. 144, 04017013 (2018). https://doi.org/10.1061/(ASCE)EI.1943-5541.0000349

    Article  Google Scholar 

  49. F.M. Bademosi, R. Tayeh, R.R.A. Issa, An Immersive Approach to Construction Cost Estimating, in ASCE International Conference on Computing in Civil Engineering 2019, (American Society of Civil Engineers, Atlanta, GA, 2019), pp. 48–54. https://doi.org/10.1061/9780784482421.007

    Chapter  Google Scholar 

  50. M. Froehlich, S. Azhar, Investigating Virtual Reality Headset Applications in Construction, in: 52nd ASC Annual International Conference Proceedings (Associated Schools of Construction, Provo, UT, 2016) http://ascpro0.ascweb.org/archives/cd/2016/paper/CPRT195002016.pdf

    Google Scholar 

  51. R.K. Soman, J.K. Whyte, A framework for cloud-based virtual and augmented reality using real-time information for construction progress monitoring, in Lean and Computing in Construction Congress, (ITC Digital Library, Heraklion, Greece, 2017), pp. 833–840. https://doi.org/10.24928/jc3-2017/0273

    Chapter  Google Scholar 

  52. A. Osello, G. Lucibello, F. Morgagni, HBIM and virtual tools: A new chance to preserve architectural heritage. Buildings 8, 12 (2018). https://doi.org/10.3390/buildings8010012

    Article  Google Scholar 

  53. Y. Mo, D. Zhao, J. Du, W. Liu, A. Dhara, Data-driven approach to scenario determination for VR-based construction safety training, in Construction Research Congress 2018, (Americana Society of Civil Engineers, New Orleans, LA, 2018), pp. 114–125. https://doi.org/10.1061/9780784481288.012

    Chapter  Google Scholar 

  54. T.H. Lin, C.H. Liu, M.H. Tsai, S.C. Kang, Using augmented reality in a multiscreen environment for construction discussion. J. Comput. Civ. Eng. 29, 04014088 (2015). https://doi.org/10.1061/(asce)cp.1943-5487.0000420

    Article  Google Scholar 

  55. P. Milgram, H. Takemura, A. Utsumi, F. Kishino, Augmented reality: A class of displays on the reality-virtuality continuum, in Photonics for Industrial Applications, (SPIE Digital Library, Boston, MA, 1995), pp. 282–292. https://doi.org/10.1117/12.197321

    Chapter  Google Scholar 

  56. A.B. Cleveland, Emerging tools to enable construction engineering. J. Constr. Eng. Manag. 137, 836–842 (2011). https://doi.org/10.1061/(asce)co.1943-7862.0000278

    Article  Google Scholar 

  57. C.S. Park, D.Y. Lee, O.S. Kwon, X. Wang, A framework for proactive construction defect management using BIM, augmented reality and ontology-based data collection template. Automat. Constr. 33, 61–71 (2013). https://doi.org/10.1016/j.autcon.2012.09.010

    Article  Google Scholar 

  58. S. Rankohi, L. Waugh, Review and analysis of augmented reality literature for construction industry. Vis. Eng. 1, 9 (2013). https://doi.org/10.1186/2213-7459-1-9

    Article  Google Scholar 

  59. X. Wang, P.E.D. Love, M.J. Kim, C.S. Park, C.P. Sing, L. Hou, A conceptual framework for integrating building information modeling with augmented reality. Automat. Constr. 34, 37–44 (2013). https://doi.org/10.1016/j.autcon.2012.10.012

    Article  Google Scholar 

  60. F.M. Bademosi, R.R.A. Issa, Business Value of Augmented Reality in the Construction Industry, in: Construction Research Congress 2018, American Society of Civil Engineers, New Orleans, LA, 2018: pp. 715–724. https://doi.org/10.1061/9780784481264.070

  61. F.M. Bademosi, N. Blinn, R.R.A. Issa, Use of augmented reality technology to enhance comprehension of construction assemblies. ITcon. 24, 58–79 (2019) http://www.itcon.org/2019/4

    Google Scholar 

  62. P.S. Dunston, X. Wang, Mixed reality-based visualization interfaces for architecture, engineering, and construction industry. J. Constr. Eng. Manag. 131, 1301–1309 (2005). https://doi.org/10.1061/(asce)0733-9364(2005)131:12(1301)

    Article  Google Scholar 

  63. H.K. Wu, S.W.Y. Lee, H.Y. Chang, J.C. Liang, Current status, opportunities and challenges of augmented reality in education. Comput. Educ. 62, 41–49 (2013). https://doi.org/10.1016/j.compedu.2012.10.024

    Article  Google Scholar 

  64. V. Stojanovic, M. Trapp, R. Richter, B. Hagedorn, J. Döllner, Towards the Generation of Digital Twins for Facility Management Based on 3D Point Clouds, in Proceedings of the 34th Annual ARCOM Conference, (Association of Researchers in Construction Management, Belfast, UK, 2018), pp. 270–279. http://www.arcom.ac.uk/-docs/proceedings/b65e593d342a8de045cf05698677e600.pdf

    Google Scholar 

  65. T. Greif, N. Stein, C.M. Flath, Peeking into the void: Digital twins for construction site logistics. Comput. Ind. 121, 103264 (2020). https://doi.org/10.1016/j.compind.2020.103264

    Article  Google Scholar 

  66. C. Kan, C.J. Anumba, Digital Twins as the Next Phase of Cyber-Physical Systems in Construction, in International Conference Computing in Civil Engineering 2019, (American Society of Civil Engineers, Atlanta, GA, 2019), pp. 256–264. https://doi.org/10.1061/9780784482438.033

    Chapter  Google Scholar 

  67. F. Bos, R. Wolfs, Z. Ahmed, T. Salet, Additive manufacturing of concrete in construction: Potentials and challenges of 3D concrete printing. Virtual Phys. Prototy. 11, 209–225 (2016). https://doi.org/10.1080/17452759.2016.1209867

    Article  Google Scholar 

  68. J. Neelamkavil, Automation in the Prefab and Modular Construction Industry, in Proceedings of the 26th International Symposium on Automation and Robotics in Construction, (The International Association for Automation and Robotics in Construction, Austin, TX, 2009), pp. 299–306. https://doi.org/10.22260/isarc2009/0018

    Chapter  Google Scholar 

  69. H.N. Saha, A. Mandal, A. Sinha, Recent Trends in the Internet of Things, in IEEE 7th Annual Computing and Communication Workshop and Conference, (Institute of Electrical and Electronics Engineers, Las Vegas, NV, 2017), pp. 1–4. https://doi.org/10.1109/CCWC.2017.7868439

    Chapter  Google Scholar 

  70. S. Greengard, The Internet of Things (MIT Press, Boston, 2015) ISBN: 9780262527736

    Book  Google Scholar 

  71. M. Negnevitisky, Artificial Intelligence A Guide to Intelligent Systems, 2nd edn. (Pearson Education Limited, Essex, 2005) ISBN: 0 321 20466 2

    Google Scholar 

  72. L. Ustinovičius, R. Rasiulis, L. Nazarko, T. Vilutiene, M. Reizgevicius, Innovative research projects in the field of building lifecycle management. Procedia Eng. 122, 166–171 (2015). https://doi.org/10.1016/j.proeng.2015.10.021

    Article  Google Scholar 

  73. J.S. Chou, C.W. Lin, A.D. Pham, J.Y. Shao, Optimized artificial intelligence models for predicting project award price. Automat. Constr. 54, 106–115 (2015). https://doi.org/10.1016/j.autcon.2015.02.006

    Article  Google Scholar 

  74. V. Faghihi, A. Nejat, K.F. Reinschmidt, J.H. Kang, Automation in construction scheduling: A review of the literature. Int. J. Adv. Manuf. Technol. 81, 1845–1856 (2015). https://doi.org/10.1007/s00170-015-7339-0

    Article  Google Scholar 

  75. D. Nozaki, K. Okamoto, T. Mochida, X. Qi, Z. Wen, S.H. Myint, K. Tokuda, T. Sato, K. Tamesue, AI Management System to Prevent Accidents in Construction Zones Using 4K Cameras Based on 5G Network, in Proceedings of the 21st International Symposium on Wireless Personal Multimedia, (Institute of Electrical and Electronics Engineers, Chiang Rai, Thailand, 2018), pp. 462–466. https://ieeexplore.ieee.org/document/8712896/

    Google Scholar 

  76. S. Golnaraghi, Z. Zangenehmadar, O. Moselhi, S. Alkass, A.R. Vosoughi, Application of artificial neural network(s) in predicting formwork labour productivity. Adv. Civ. Eng. 2019, 5972620 (2019). https://doi.org/10.1155/2019/5972620

    Article  Google Scholar 

  77. P. Mell, T. Grance, Appendix C - The NIST definition of cloud computing, in: R. Strum, C. Pollard, J. Craig (eds), Application Performance Management (APM) in the Digital Enterprise, Kauffman, 2017: pp. 267–269. https://doi.org/10.1016/b978-0-12-804018-8.15003-x

  78. M. Bilal, L.O. Oyedele, O.O. Akinade, S.O. Ajayi, H.A. Alaka, H.A. Owolabi, J. Qadir, M. Pasha, S.A. Bello, Big data architecture for construction waste analytics (CWA): A conceptual framework. J. Build. Eng. 6, 144–156 (2016). https://doi.org/10.1016/j.jobe.2016.03.002

    Article  Google Scholar 

  79. J. McMalcolm, How Big Data Is Transforming the Construction Industry (Construction Global, 2015) https://www.constructionglobal.com/technology-and-ai-1/how-big-data-is-transforming-the-construction-industry. Accessed 10.10.19

    Google Scholar 

  80. S. Krish, A practical generative design method. Comput. Aided Des. 43, 88–100 (2011). https://doi.org/10.1016/j.cad.2010.09.009

    Article  Google Scholar 

  81. E. Rodrigues, N. Soares, M.S. Fernandes, A.R. Gaspar, Á. Gomes, J.J. Costa, An integrated energy performance-driven generative design methodology to foster modular lightweight steel framed dwellings in hot climates. Energy Sustain. Dev. 44, 21–36 (2018). https://doi.org/10.1016/j.esd.2018.02.006

    Article  Google Scholar 

  82. P. Tang, X. Wang, X. Shi, Generative design method of the facade of traditional architecture and settlement based on knowledge discovery and digital generation: A case study of Gunanjie Street in China. Int. J of Archit. Herit. 13, 679–690 (2019). https://doi.org/10.1080/15583058.2018.1463415

    Article  Google Scholar 

  83. E. Touloupaki, T. Theodosiou, Energy performance optimization as a generative design tool for nearly zero energy buildings. Proc. Eng. 180, 1178–1185 (2017). https://doi.org/10.1016/j.proeng.2017.04.278

    Article  Google Scholar 

  84. E. Francalanza, A. Fenech, P. Cutajar, Generative design in the development of a robotic manipulator. Proc. CIRP 67, 244–249 (2018). https://doi.org/10.1016/j.procir.2017.12.207

    Article  Google Scholar 

  85. K.B. Sørensen, P. Christiansson, K. Svidt, Ontologies to support RFID-based link between virtual models and construction components. Comput. Aided Civ. Infrastr. Eng. 25, 285–302 (2010). https://doi.org/10.1111/j.1467-8667.2009.00638.x

    Article  Google Scholar 

  86. J. Majrouhi Sardroud, Influence of RFID technology on automated management of construction materials and components. Scien. Iranica. 19, 381–392 (2012). https://doi.org/10.1016/j.scient.2012.02.023

    Article  Google Scholar 

  87. M. Roberti, How is RFID being used in the construction industry? (Ask Experts Forum, RFID Journal, 2013) https://www.rfidjournal.com/question/how-is-rfid-being-used-in-the-construction-industry. Accessed 08.09.19

    Google Scholar 

  88. F. Fang, S. Aabith, S. Homer-Vanniasinkam, M.K. Tiwari, High-resolution 3D printing for healthcare underpinned by small-scale fluidics. 3D Print Med., 167–206 (2017). https://doi.org/10.1016/B978-0-08-100717-4.00023-5

  89. OSHA – Occupational Safety and Health Administration, Commonly Used Statistics (OSHA Training Institute, 2018) https://www.osha.gov/data/commonstats. Accessed 01.02.19

    Google Scholar 

  90. I. Awolusi, E. Marks, M. Hallowell, Wearable technology for personalized construction safety monitoring and trending: Review of applicable devices. Automat. Constr. 85, 96–106 (2018). https://doi.org/10.1016/j.autcon.2017.10.010

    Article  Google Scholar 

  91. J.A. Romero, A.A. Lozano-Guzmán, E. Betanzo-Quezada, C.S. López-Cajún, Robotics and road transportation: A review, in Intelligent Robotics and Applications, ICIRA 2014, Lecture Notes in Computer Science, ed. by X. Zhang, H. Liu, Z. Chen, N. Wang, vol. 8917, (Springer, Cham, 2014). https://doi.org/10.1007/978-3-319-13966-1_46

    Chapter  Google Scholar 

  92. K.S. Saidi, T. Bock, C. Georgoulas, Robotics in construction, in Springer Handbook of Robotics, Springer Handbooks, ed. by B. Siciliano, O. Khatib, (Springer, Cham, 2016). https://doi.org/10.1007/978-3-319-32552-1_57

    Chapter  Google Scholar 

  93. Q. Chen, B. García de Soto, B.T. Adey, Construction automation: Research areas, industry concerns and suggestions for advancement. Automat. Constr. 94, 22–38 (2018). https://doi.org/10.1016/j.autcon.2018.05.028

    Article  Google Scholar 

  94. J. Werfel, K. Petersen, R. Nagpal, Designing collective behavior in a termite-inspired robot construction team. Science 342, 754–758 (2014). https://doi.org/10.1126/science.1245842

    Article  Google Scholar 

  95. S. Goessens, C. Mueller, P. Latteur, Feasibility study for drone-based masonry construction of real-scale structures. Automat. Constr. 94, 458–480 (2018). https://doi.org/10.1016/j.autcon.2018.06.015

    Article  Google Scholar 

  96. J.M. Davila Delgado, L. Oyedele, A. Ajayi, L. Akanbi, O. Akinade, M. Bilal, H. Owolabi, Robotics and automated systems in construction: Understanding industry-specific challenges for adoption. J. Build. Eng. 26, 100868 (2019). https://doi.org/10.1016/j.jobe.2019.100868

    Article  Google Scholar 

  97. X. Zhang, M. Li, J.H. Lim, Y. Weng, Y.W.D. Tay, H. Pham, Q.C. Pham, Large-scale 3D printing by a team of mobile robots. Automat. Constr. 95, 98–106 (2018). https://doi.org/10.1016/j.autcon.2018.08.004

    Article  Google Scholar 

  98. A.G. Gibb, Off-Site Fabrication: Prefabrication, Pre-Assembly and Modularisation (Wiley, 1999) ISBN: 0-470-37836-0

    Google Scholar 

  99. J. Wang, S.N. Razavi, Low false alarm rate model for unsafe-proximity detection in construction. J. Comput. Civ. Eng. 30, 04015005 (2016). https://doi.org/10.1061/(asce)cp.1943-5487.0000470

    Article  Google Scholar 

  100. D. Delgado Camacho, P. Clayton, W.J. O’Brien, C. Seepersad, M. Juenger, R. Ferron, S. Salamone, Applications of additive manufacturing in the construction industry – A forward-looking review. Automat. Constr. 89, 110–119 (2018). https://doi.org/10.1016/j.autcon.2017.12.031

    Article  Google Scholar 

  101. E.R. Azar, V.R. Kamat, Earthmoving equipment automation: A review of technical advances and future outlook. ITcon. 22(2017), 247–265 (2017) https://www.itcon.org/2017/13

    Google Scholar 

  102. CPWR – The Center for Construction Research and Training, Fatal Injuries at Road Construction Sites Among Construction Workers (CPWR – The Center for Construction Research and Training. https://www.cpwr.com/update_newsletter/fatal-injuries-at-road-construction-sites-among-construction-workers-a-cpwr-quarterly-data-report/. Accessed 11.10.18, 2018)

    Google Scholar 

  103. Bureau of Labor Statistics, Fatal Occupational Injuries by Industry and Event or Exposure (all United States, 2019) https://www.bls.gov/iif/oshwc/cfoi/cftb0331.htm. Accessed 07.10.19

    Google Scholar 

  104. Built Robotics, Robots that build the world 2021. http://www.builtrobotics.com/. Accessed 03.01.21

    Google Scholar 

  105. S. Dadhich, U. Bodin, U. Andersson, Key challenges in automation of earth-moving machines. Automat. Constr. 68, 212–222 (2016). https://doi.org/10.1016/j.autcon.2016.05.009

    Article  Google Scholar 

  106. J. Kim, S.S. Lee, J. Seo, V.R. Kamat, Modular data communication methods for a robotic excavator. Automat. Constr. 90, 166–177 (2018). https://doi.org/10.1016/j.autcon.2018.02.007

    Article  Google Scholar 

  107. J.G. Martinez, G. Albeaino, M. Gheisari, W. Volkmann, L.F. Alarcón, UAS point cloud accuracy assessment using structure from motion–based photogrammetry and PPK georeferencing technique for building surveying applications. J. Comput. Civ. Eng. 35, 05020004 (2021). https://doi.org/10.1061/(asce)cp.1943-5487.0000936

    Article  Google Scholar 

  108. F. Elghaish, S. Matarneh, S. Talebi, M. Kagioglou, M.R. Hosseini, S. Abrishami, Toward digitalization in the construction industry with immersive and drones technologies: a critical literature review. Smart Sustain, Built Environ. ahead-of-print (2020). https://doi.org/10.1108/SASBE-06-2020-0077

  109. S. Agnisarman, S. Lopes, K. Chalil Madathil, K. Piratla, A. Gramopadhye, A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection. Automat. Constr. 97, 52–76 (2018). https://doi.org/10.1016/j.autcon.2018.10.019

    Article  Google Scholar 

  110. J.J. Lin, A. Ibrahim, S. Sarwade, M. Golparvar-Fard, Bridge inspection with aerial robots: Automating the entire pipeline of visual data capture, 3D mapping, defect detection, analysis, and reporting. J. Comput. Civ. Eng. 35, 04020064 (2021). https://doi.org/10.1061/(ASCE)CP.1943-5487.0000954

    Article  Google Scholar 

  111. T. Nasiruddin Khilji, L.L.A. Loures, E.R. Azar, Distress recognition in unpaved roads using unmanned aerial systems and deep learning segmentation. J. Comput. Civ. Eng. 35, 04020061 (2021). https://doi.org/10.1061/(asce)cp.1943-5487.0000952

    Article  Google Scholar 

  112. S. Kim, Y. Gan, J. Irizarry, Framework for UAS-integrated airport runway design code compliance using incremental mosaic imagery. J. Comput. Civ. Eng. 35, 04020070 (2021). https://doi.org/10.1061/(ASCE)CP.1943-5487.0000960

    Article  Google Scholar 

  113. D. Liu, X. Xia, J. Chen, S. Li, Integrating building information model and augmented reality for drone-based building inspection. J. Comput. Civ. Eng. 35, 04020073 (2021). https://doi.org/10.1061/(ASCE)CP.1943-5487.0000958

    Article  Google Scholar 

  114. J. Park, K. Kim, Y.K. Cho, Framework of automated construction-safety monitoring using cloud-enabled BIM and BLE mobile tracking sensors. J. Constr. Eng. Manag. 143, 04020073 (2017). https://doi.org/10.1061/(asce)co.1943-7862.0001223

    Article  Google Scholar 

  115. M. Akinlolu, T.C. Haupt, D.J. Edwards, F. Simpeh, A bibliometric review of the status and emerging research trends in construction safety management technologies. Int. J. Constr. Manage. ahead-of-print (2020). https://doi.org/10.1080/15623599.2020.1819584

  116. M. Gheisari, A. Rashidi, B. Esmaeili, Using unmanned aerial systems for automated fall hazard monitoring, in Proceedings of Construction Research Congress 2018, (American Society of Civil Engineers, New Orleans, LA, 2018), pp. 62–72. https://doi.org/10.1061/9780784481288.007

    Chapter  Google Scholar 

  117. Y. Fang, Y.K. Cho, S. Zhang, E. Perez, Case study of BIM and cloud–enabled real-time RFID indoor localization for construction management applications. J. Constr. Eng. Manag. 142, 05016003 (2016). https://doi.org/10.1061/(asce)co.1943-7862.0001125

    Article  Google Scholar 

  118. M. Wang, C.C. Wang, S. Sepasgozar, S. Zlatanova, A systematic review of digital technology adoption in off-site construction: Current status and future direction towards industry 4.0. Buildings 10, 204 (2020). https://doi.org/10.3390/buildings10110204

    Article  Google Scholar 

  119. J. Louis, P.S. Dunston, Integrating IoT into operational workflows for real-time and automated decision-making in repetitive construction operations. Automat. Constr. 94, 317–327 (2018). https://doi.org/10.1016/j.autcon.2018.07.005

    Article  Google Scholar 

  120. C. Ning, F. You, Data-driven decision making under uncertainty integrating robust optimization with principal component analysis and kernel smoothing methods. Comput. Chem. Eng. 112, 190–210 (2018). https://doi.org/10.1016/j.compchemeng.2018.02.007

    Article  Google Scholar 

  121. V. Kulkarni, R. Sharma, M. Hote, M.E. Civil, Factors affecting material management on construction site. IRJET. 4, 474–478 (2017) https://www.irjet.net/archives/V4/i1/IRJET-V4I178.pdf

    Google Scholar 

  122. N. Kasim, N. Sarpin, H. Mohd Noh, R. Zainal, S. Mohamed, N. Manap, M.Y. Yahya, Automatic materials tracking practices through RFID implementation in construction projects, in International Conference on Built Environment and Engineering, (MATEC Web of Conferences, Johor, Malaysia, 2019), p. 050001. https://doi.org/10.1051/matecconf/201926605001

    Chapter  Google Scholar 

  123. US EPA – United States Environmental Protection Agency, Advancing Sustainable Materials Management: 2017 Fact Sheet (United States Environmental Protection Agency, Office of Land and Emergency Management, Washington, DC, 2019), p. 20460. https://www.epa.gov/facts-and-figures-about-materials-waste-and-recycling/advancing-sustainable-materials-management. Accessed 09.09.19

    Google Scholar 

  124. M. Pan, T. Linner, W. Pan, H. Cheng, T. Bock, A framework of indicators for assessing construction automation and robotics in the sustainability context. J. Clean. Prod. 182, 82–95 (2018). https://doi.org/10.1016/j.jclepro.2018.02.053

    Article  Google Scholar 

  125. S. Lee, W. Pan, T. Linner, T. Bock, A framework for robot assisted deconstruction: process, sub-systems and modelling, in Proceedings of the 32nd International Symposium on Automation and Robotics in Construction, (The International Association for Automation and Robotics in Construction, Oulu, Finland, 2015), pp. 1–8. https://doi.org/10.22260/isarc2015/0093

    Chapter  Google Scholar 

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Bademosi, F.M., Issa, R.R.A. (2022). Automation and Robotics Technologies Deployment Trends in Construction. In: Jebelli, H., Habibnezhad, M., Shayesteh, S., Asadi, S., Lee, S. (eds) Automation and Robotics in the Architecture, Engineering, and Construction Industry. Springer, Cham. https://doi.org/10.1007/978-3-030-77163-8_1

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