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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
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
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
United Nations, World Urbanization Prospects 2018, illustrated revised ed., United Nations Publications, UN, 2019. ISBN 9211483190, 9789211483192
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
Bureau of Labor Statistics, Integrated BLS-BEA Industry-Level Production Account Tables. https://www.bls.gov/mfp/indprod11.xlsx, 2018. Accessed 02.27.2021
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
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
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
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
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
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
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
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
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
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
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
Merriam-Webster, Robot | Definition of Robot by Merriam-Webster (Merriam-Webster, 2018) https://www.merriam-webster.com/dictionary/robot. Accessed 10.10.18
R. Rennie, J. Law (eds.), A Dictionary of Physics, 8th edn. (Oxford University Press, 2019). https://doi.org/10.1093/acref/9780198821472.001.0001
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
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
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
A. Kerr (ed.), Dictionary of World History, 3rd edn. (Oxford University Press, Oxford, 2015). https://doi.org/10.1093/acref/9780199685691.001.0001
World Encyclopedia (Phillip’s, Oxford, 2014). https://doi.org/10.1093/acref/9780199546091.001.0001
Merriam-Webster, Automation | Definition of Automation by Merriam-Webster (Merriam-Webster, 2018) https://www.merriam-webster.com/dictionary/automation. Accessed 10.10.18
J. Scott, G. Marshall, A Dictionary of Sociology, 3rd edn. (Oxford University Press, Oxford, 2009). https://doi.org/10.1093/acref/9780199533008.001.0001
M. Rajgor, J. Pitroda, Automation: A new millennium technology for construction industries. Global Res. Anal. 9, 79–81 (2013) ISSN 2277-8160
C. Soanes, A. Stevenson (eds.), Concise Oxford English Dictionary, 11th edn. (Oxford University Press, Oxford, 2005) ISBN-10: 019861-475
Merriam-Webster, Construction | Definition of Construction by Merriam-Webster (Merriam-Webster, 2018) https://www.merriam-webster.com/dictionary/construction. Accessed 10.10.18
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
T. Bock, T. Linner, Construction Robots: Elementary Technologies and Single-Task Construction Robots (Cambridge University Press, Cambridge, 2017). https://doi.org/10.1017/CBO9781139872041
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
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
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
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
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
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
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)
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
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
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
Doxel, Artificial intelligence for construction productivity (2020). https://www.doxel.ai. Accessed 10.09.19
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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
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
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
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
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
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
S. Greengard, The Internet of Things (MIT Press, Boston, 2015) ISBN: 9780262527736
M. Negnevitisky, Artificial Intelligence A Guide to Intelligent Systems, 2nd edn. (Pearson Education Limited, Essex, 2005) ISBN: 0 321 20466 2
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
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
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
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/
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
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
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
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
S. Krish, A practical generative design method. Comput. Aided Des. 43, 88–100 (2011). https://doi.org/10.1016/j.cad.2010.09.009
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
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
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
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
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
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
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
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
OSHA – Occupational Safety and Health Administration, Commonly Used Statistics (OSHA Training Institute, 2018) https://www.osha.gov/data/commonstats. Accessed 01.02.19
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
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
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
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
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
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
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
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
A.G. Gibb, Off-Site Fabrication: Prefabrication, Pre-Assembly and Modularisation (Wiley, 1999) ISBN: 0-470-37836-0
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
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
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
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)
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
Built Robotics, Robots that build the world 2021. http://www.builtrobotics.com/. Accessed 03.01.21
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-77163-8_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77162-1
Online ISBN: 978-3-030-77163-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)