Rethinking engineering management for human–robot collaboration from technological and social perspectives

Abstract

The rapid evolution of robotic and intelligent technologies is propelling the construction industry toward human–robot collaboration. Consequently, robots have transcended their role as mere instruments of labor to acquire the attributes of laborers, forming a human–robot hybrid workforce that jointly undertakes productive activities. The emergence of this new labor paradigm is poised to trigger unprecedented transformations in project division of labor, organizational structure, technological coordination, management models, and governance mechanisms. However, existing research lacks a systematic understanding of this transformation and its potential cascading effects. Therefore, this paper adopts a sociotechnical systems framework to analyze human–robot collaboration, examining the technological evolution of construction robots from tools to partners and the corresponding shifts in collaboration patterns. Furthermore, drawing on the Leavitt model, human–robot collaboration is conceptualized as a coupled configuration of “people–technology–task–structure.” This perspective enables an integrated analysis of how the technical and social attributes of human–robot collaboration reshape both the technical logic and managerial paradigms of engineering management. Finally, this study identifies ten key research topics reflecting the emerging characteristics of human–robot collaboration in the construction industry, aiming to illuminate future frontiers of this transformation in engineering management.

Graphical abstract

Keywords

human–robot collaboration / engineering management / sociotechnical system

References

[1] Abioye S O, Oyedele L O, Akanbi L, Ajayi A, Davila Delgado J M, Bilal M, Akinade O O, Ahmed A, (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44: 103299

[2] Alsakka F, Yu H, El-Chami I, Hamzeh F, Al-Hussein M, (2024). Digital twin for production estimation, scheduling and real-time monitoring in offsite construction. Computers & Industrial Engineering, 191: 110173

[3] Angelopoulos A, Cahoon J F, Alterovitz R, (2024). Transforming science labs into automated factories of discovery. Science Robotics, 9( 95): eadm6991

[4] Asea Brown Boveri (2021). ABB Robotics 2021 Construction Survey. Available at the website of express.adobe.com

[5] Bai X, He S, Li Y, Xie Y, Zhang X, Du W, Li J R, (2025). Construction of a knowledge graph for framework material enabled by large language models and its application. npj Computational Materials, 11( 1): 51

[6] Bruun E P G, Oval R, Al Asali W, Gáspár O, Paris V, Adriaenssens S, (2024). Automating historical centering-minimizing masonry vaulting strategies: Applications to cooperative robotic construction. Developments in the Built Environment, 20: 100516

[7] Callari T C, Vecellio Segate R, Hubbard E M, Daly A, Lohse N, (2024). An ethical framework for human–robot collaboration for the future people-centric manufacturing: A collaborative endeavour with European subject-matter experts in ethics. Technology in Society, 78: 102680

[8] Chae H, Moon Y, Lee K, Park S, Kim H S, Seo T, (2022). A tethered façade cleaning robot based on a dual rope windlass climbing mechanism: Design and experiments. IEEE/ASME Transactions on Mechatronics, 27( 4): 1982–1989

[9] Charalambous G, Fletcher S, Webb P, (2016). The development of a scale to evaluate trust in industrial human–robot collaboration. International Journal of Social Robotics, 8( 2): 193–209

[10] Chen X, Huang H, Liu Y, Li J, Liu M, (2022). Robot for automatic waste sorting on construction sites. Automation in Construction, 141: 104387

[11] Chen Z, Adel A, (2025). Advancing robotic assembly in construction: Innovations, challenges, and opportunities. Automation in Construction, 178: 106370

[12] Deepa R, Sekar S, Malik A, Kumar J, Attri R, (2024). Impact of AI-focussed technologies on social and technical competencies for HR managers—A systematic review and research agenda. Technological Forecasting and Social Change, 202: 123301

[13] Dixon J, Hong B, Wu L, (2021). The robot revolution: Managerial and employment consequences for firms. Management Science, 67( 9): 5586–5605

[14] Duan K, Zou Z, (2025). Safety-constrained deep reinforcement learning control for human–robot collaboration in construction. Automation in Construction, 174: 106130

[15] Fischer B, Frennert S, (2025). Towards an experiential ethics of AI and robots: A review of empirical research on human encounters. Technological Forecasting and Social Change, 219: 124264

[16] Fu Y, Chen J, Lu W, (2024). Human–robot collaboration for modular construction manufacturing: Review of academic research. Automation in Construction, 158: 105196

[17] Funk N, Menzenbach S, Chalvatzaki G, Peters J, (2022). Graph-based reinforcement learning meets mixed integer programs: An application to 3D robot assembly discovery. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2022: 10215–10222

[18] Gasparetto A, Scalera L, (2019). A brief history of industrial robotics in the 20th century. Advances in Historical Studies, 8( 1): 24–35

[19] Heuthe V L, Panizon E, Gu H, Bechinger C, (2024). Counterfactual rewards promote collective transport using individually controlled swarm microrobots. Science Robotics, 9( 97): eado5888

[20] Jia Z, Xie S, Zhang W, (2025). Flexible task assignment and assembly scheduling for human–robot collaboration cell considering uncertainty. International Journal of Production Research, 63( 16): 6134–6154

[21] Jiang Y, Li M, Li M, Liu X, Zhong R Y, Pan W, Huang G Q, (2022). Digital twin-enabled real-time synchronization for planning, scheduling, and execution in precast on-site assembly. Automation in Construction, 141: 104397

[22] Karakikes M, Nathanael D, (2023). The effect of cognitive workload on decision authority assignment in human–robot collaboration. Cognition Technology and Work, 25( 1): 31–43

[23] Kirtay M, Hafner V V, Asada M, Oztop E, (2023). Trust in robot–robot scaffolding. IEEE Transactions on Cognitive and Developmental Systems, 15( 4): 1841–1852

[24] Leavitt H J, (1965). Applied organizational change in industry: Structural, technological and humanistic Approaches. In: Handbook of Organizations (RLE: Organizations). Routledge, 2013: 1144–1170

[25] Lee D, Han K, (2024). Vision-based construction robot for real-time automated welding with human-robot interaction. Automation in Construction, 168: 105782

[26] Lemonnier P, (1986). The study of material culture today: Toward an anthropology of technical systems. Journal of Anthropological Archaeology, 5( 2): 147–186

[27] Li Z, Yu Y, Zeng N, Tian F, Zhang S, Sun H, Li Q, (2025). Human-centric human–robot collaboration in on-site construction (2014–2024): Advances, barriers, and future directions. Automation in Construction, 180: 106566

[28] Liang C J, Wang X, Kamat V R, Menassa C C, (2021). Human–robot collaboration in construction: classification and research trends. Journal of Construction Engineering and Management, 147( 10): 03121006

[29] Liu J, Luo H, Wu D, (2025). Human–robot collaboration in construction: Robot design, perception and Interaction, and task allocation and execution. Advanced Engineering Informatics, 65: 103109

[30] Liu Y, Fan J, Zhao L, Shen W, Zhang C, (2023). Integration of deep reinforcement learning and multi-agent system for dynamic scheduling of re-entrant hybrid flow shop considering worker fatigue and skill levels. Robotics and Computer-integrated Manufacturing, 84: 102605

[31] Lu W, Lou J, Ababio BK, Zhong RY, Bao Z, Li X, Xue F, (2024). Digital technologies for construction sustainability: Status quo, challenges, and future prospects. npj Materials Sustainability, 2( 1): 10

[32] Ma X, Mao C, Liu G, (2022). Can robots replace human beings? —Assessment on the developmental potential of construction robot. Journal of Building Engineering, 56: 104727

[33] Martinez Lagunas A J, Nik-Bakht M, (2024). Process mining, Modeling, and management in construction: A critical review of three decades of research coupled with a current industry perspective. Journal of Construction Engineering and Management, 150( 11): 04024158

[34] McKinsey & Company (2017). A future that works: Automation, employment, and productivity. Available at the website of mckinsey.com

[35] McKinsey & Company (2023). Unlocking the industrial potential of robotics and automation. Available at the website of mckinsey.com

[36] Melenbrink N, Werfel J, Menges A, (2020). On-site autonomous construction robots: Towards unsupervised building. Automation in Construction, 119: 103312

[37] Meng Y, Bing Z, Yao X, Chen K, Huang K, Gao Y, Sun F, Knoll A, (2025). Preserving and combining knowledge in robotic lifelong reinforcement learning. Nature Machine Intelligence, 7( 2): 256–269

[38] Ojha A, Liu Y, Shayesteh S, Jebelli H, Sitzabee W E, (2023). Affordable multiagent robotic system for same-level fall hazard detection in indoor construction environments. Journal of Computing in Civil Engineering, 37( 1): 04022042

[39] Olukanni EAkanmu AJebelli H (2025). Industry perception of competencies for human—robot collaboration in the construction industry: A Delphi study. Frontiers of Engineering Management, 1–26

[40] Parascho S, (2023). Construction robotics: From automation to collaboration. Annual review of control, robotics, and autonomous systems, 6: 183–204

[41] Ragan J, Riviere B, Hadaegh F Y, Chung S J, (2024). Online tree-based planning for active spacecraft fault estimation and collision avoidance. Science Robotics, 9( 93): eadn4722

[42] Robot planning with LLMs, (2025). Robot planning with LLMs. Nature Machine Intelligence, 7( 4): 521–521

[43] Rodrigues P B, Singh R, Oytun M, Adami P, Woods P J, Becerik-Gerber B, Soibelman L, Copur-Gencturk Y, Lucas G M, (2023). A multidimensional taxonomy for human-robot interaction in construction. Automation in Construction, 150: 104845

[44] Vecellio Segate R, Daly A, (2024). Encoding the enforcement of safety standards into smart robots to harness their computing sophistication and collaborative potential: A legal risk assessment for European Union policymakers. European Journal of Risk Regulation, 15( 3): 665–704

[45] Shakeri Z, Benfriha K, Varmazyar M, Talhi E, Quenehen A, (2025). Production scheduling with multi-robot task allocation in a real industry 4.0 setting. Scientific Reports, 15( 1): 1795

[46] Sun Y, Wang L, Ni Y, Zhang H, Cui X, Li J, Zhu Y, Liu J, Zhang S, Chen Y, Li M, (2023). 3D printing of thermosets with diverse rheological and functional applicabilities. Nature Communications, 14( 1): 245

[47] Tarafdar M, Page X, Marabelli M, (2023). Algorithms as co-workers: Human algorithm role interactions in algorithmic work. Information Systems Journal, 33( 2): 232–267

[48] Torras C, (2024). Ethics of social robotics: Individual and societal concerns and opportunities. Annual Review of Control, Robotics, and Autonomous Systems, 7: 1–18

[49] Tsvetkova M, Yasseri T, Pescetelli N, Werner T, (2024). A new sociology of humans and machines. Nature Human Behaviour, 8( 10): 1864–1876

[50] Wang H, (2021). The history, characteristics, program and value of anthropology of Technology. Studies in Dialectics of Nature, 37( 04): 43–48 (in Chinese)

[51] Wang H, Li J, Liu J, Fan Y, Ma L, Huo H, Liu Z, Ding L, (2023). Research on human–machine integration complex social system. Chinese Journal of Management Science, 31( 7): 1–21 (in Chinese)

[52] Wang J, Shi E, Hu H, Ma C, Liu Y, Wang X, Yao Y, Liu X, Ge B, Zhang S, (2025a). Large language models for robotics: Opportunities, challenges, and perspectives. Journal of Automation and Intelligence, 4( 1): 52–64

[53] Wang M, Cai J, Hu D, Hu Y, Han Z, Li S, (2025b). AI-based robots in industrialized building manufacturing. Frontiers of Engineering Management, 12( 1): 59–85

[54] Wang X, Liang C J, Menassa C C, Kamat V R, (2021). Interactive and immersive process-level digital twin for collaborative human–robot construction work. Journal of Computing in Civil Engineering, 35( 6): 04021023

[55] Wang X, Wang J, Wu C, Xu S, Ma W, (2022). Engineering brain: Metaverse for future engineering. AI in Civil Engineering, 1( 1): 2

[56] Weng Y HTorabi DTorresen JDong ZHirata Y (2025). Bridging Ethics and Reality: Integrating Thought Experiments and Empirical Insights in Robot Ethics. IEEE Robotics & Automation Magazine: 2–8

[57] Xiang S, Wang R, Feng C, (2021). Mobile projective augmented reality for collaborative robots in construction. Automation in Construction, 127: 103704

[58] Xiong W, Fan H, Ma L, Wang C, (2022). Challenges of human—machine collaboration in risky decision-making. Frontiers of Engineering Management, 9( 1): 89–103

[59] Xu Z, Song T, Guo S, Peng J, Zeng L, Zhu M, (2022). Robotics technologies aided for 3D printing in construction: A review. International Journal of Advanced Manufacturing Technology, 118( 11–12): 3559–3574

[60] Xue B, Zou L, (2023). Knowledge graph quality management: A comprehensive survey. IEEE Transactions on Knowledge and Data Engineering, 35( 5): 4969–4988

[61] Yao QMao CWang TZhang BYan RSun B (2025). Evaluating framework for the capability of construction robots. Engineering, Construction, and Architectural Management, doi:10.1108/ECAM-10-2024-1415

[62] Zeng F, Cai X, Ge S S, (2020). Low-shot wall defect detection for autonomous decoration robots using deep reinforcement learning. Journal of Robotics, 2020( 1): 8866406

[63] Zeng F, Fan C, Shirafuji S, Wang Y, Nishio M, Ota J, (2025). Task allocation and scheduling to enhance human–robot collaboration in production line by synergizing efficiency and fatigue. Journal of Manufacturing Systems, 80: 309–323

[64] Zhang K, Chermprayong P, Xiao F, Tzoumanikas D, Dams B, Kay S, Kocer B B, Burns A, Orr L, Alhinai T, Choi C, Darekar D D, Li W, Hirschmann S, Soana V, Ngah S A, Grillot C, Sareh S, Choubey A, Margheri L, Pawar V M, Ball R J, Williams C, Shepherd P, Leutenegger S, Stuart-Smith R, Kovac M, (2022). Aerial additive manufacturing with multiple autonomous robots. Nature, 609( 7928): 709–717

[65] Zhang M, Xu R, Wu H, Pan J, Luo X, (2023). Human–robot collaboration for on-site construction. Automation in Construction, 150: 104812

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