Building the Future: Robotic and Automation in Construction Industry
DOI:
https://doi.org/10.15662/IJEETR.2026.0802157Keywords:
3D printing, Underwater waste detection, deep learning, object detection, RoboticsAbstract
The construction industry, traditionally reliant on manual labor and conventional processes, is undergoing a transformative shift with the integration of robotics and automation. This technological evolution aims to enhance productivity, safety, and precision while addressing challenges such as labor shortages, project delays, and rising costs. Robotics applications in construction include automated bricklaying, 3D printing of structures, drone-based site monitoring, and robotic machinery for heavy lifting and repetitive tasks. Automation streamlines project management through smart systems, real-time data analysis, and predictive maintenance, enabling efficient resource allocation and reducing human error. This paper explores the current advancements, practical implementations, and potential impacts of robotic and automated systems on construction workflows. By adopting these innovations, the construction sector is positioned to achieve faster project delivery, improved quality, and sustainable practices, ultimately building the future of infrastructure development
References
1. Bos, F. P., Wolfs, R. J. M., Ahmed, Z. Y., & Salet, T. A. M. (2016). "Additive manufacturing of concrete in construction: Potentials and challenges." Cement and Concrete Research, 89, 241-254.
2. Kumar, V. R. P., Balasubramanian, M., & Jagadish Raj, S. (2016). “Robotics in Construction Industry.” Indian Journal of Science and Technology, 9(23). SRS Journal
3. Oesterreich, T. D., & Teuteberg, F. (2016). "Understanding the implications of digitization and automation in the construction industry." Computers in Industry, 83, 121-139.
4. Bogue, R. (2018). "Robots in the construction industry: The future is here." Industrial Robot: An International Journal, 45(6), 411-416.
5. Roca, D., Hurtado, J. E., & Crespo, L. (2019). "Unmanned aerial vehicles (UAVs) in construction: Applications, challenges, and opportunities." Automation in Construction, 103, 36-49.
6. Chea, C. P., Bai, Y., Pan, X., Arashpour, M., & Xie, Y. (2020). “An integrated review of automation and robotic technologies for structural prefabrication and construction.” Transportation Safety and Environment, 2(2), 81 96. OUP Academic
7. Lu, N., Fung, I., & Peng, Z. (2020). "Automation and prefabrication in modular construction: A comprehensive review." Journal of Construction Engineering and Management, 146(6), 04020059.
8. Nath, A. S. (2022). A Review of Advancements in Robotic and Sensor based Technologies in Construction Sector. European Journal of Engineering and Technology Research, 7(1), Article 2624. ej-eng.org
9. Xiao, B., Chen, C., & Yin, X. (2022). “Recent advancements of robotics in construction.” Automation in Construction, 144, 104591. ris.utwente.nl
10. C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746
11. C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2
12. C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9
13. Sulthana, A. R., & Murugeswari, B. (2011, March). ARIPSO: Association rule interactive postmining using schemas and ontologies. In 2011 International Conference on Emerging Trends in Electrical and Computer Technology (pp. 941-946). IEEE.
14. Anbazhagan, K. (2025). Next-Generation Enterprise Cloud AI for Healthcare: Secure CNN Pipelines and Privacy Controls. International Journal of Future Innovative Science and Technology (IJFIST), 8(6), 15980.
15. Mathew, A. (2023). Learning Metaverse Powered by Artificial Intelligence. Recent Progress in Science and Technology Vol. 4, 4, 134-141.
16. S.Tamilselvi, R.Prakash, C.Nagarajan,“Solar System Integrated Smart Grid Utilizing Hybrid Coot-Genetic Algorithm Optimized ANN Controller” Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, DOI10.1007/s40998-025-00917-z,2025
17. S.Tamilselvi, R.Prakash, C.Nagarajan,“ Adaptive sliding mode control of multilevel grid-connected inverters using reinforcement learning for enhanced LVRT performance” Electric Power Systems Research 253 (2026) 112428, doi.org/10.1016/j.epsr.2025.112428
18. S.Thirunavukkarasu, C. Nagarajan, 2024, “Performance Investigation on OCF and SCF study in BLDC machine using FTANN Controller," Journal of Electrical Engineering And Technology, Volume 20, pages 2675–2688, (2025), doi.org/10.1007/s42835-024-02126-w
19. C. Nagarajan, M.Madheswaran and D.Ramasubramanian- ‘Development of DSP based Robust Control Method for General Resonant Converter Topologies using Transfer Function Model’- Acta Electrotechnica et Informatica Journal , Vol.13 (2), pp.18-31,April-June.2013, DOI: 10.2478/aeei-2013-0025.
20. C.Nagarajan and M.Madheswaran - ‘DSP Based Fuzzy Controller for Series Parallel Resonant converter’- Springer, Frontiers of Electrical and Electronic Engineering, Vol. 7(4), pp. 438-446, Dec.12. DOI 10.1007/s11460-012-0212-0.
21. C.Nagarajan and M.Madheswaran - ‘Experimental Study and steady state stability analysis of CLL-T Series Parallel Resonant Converter with Fuzzy controller using State Space Analysis’- Iranian Journal of Electrical & Electronic Engineering, Vol.8 (3), pp.259-267, September 2012.
22. C.Nagarajan and M.Madheswaran, “Analysis and Simulation of LCL Series Resonant Full Bridge Converter Using PWM Technique with Load Independent Operation” has been presented in ICTES’08, a IEEE / IET International Conference organized by M.G.R.University, Chennai.Vol.no.1, pp.190-195, Dec.2007
23. Suganthi Mullainathan, Ramesh Natarajan, “An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques”, Revista Materia (Rio J.) Vol. 30, 2025, DOI: https://doi.org/10.1590/1517-7076-RMAT-2024-0721
24. M Suganthi, N Ramesh, “Treatment of water using natural zeolite as membrane filter”, Journal of Environmental Protection and Ecology, Volume 23, Issue 2, pp: 520-530,2022
25. Parascho, S. (2023). Construction Robotics: From Automation to Collaboration. Annual Review of Control, Robotics, and Autonomous Systems, 6, 183 204. Annual Reviews
26. Halder, S., & Afsari, K. (2023). “Robots in Inspection and Monitoring of Buildings and Infrastructure: A Systematic Review.” Applied Sciences, 13(4), 2304. MDPI
