Understanding Cognitive Impacts of Robots in Worker-Robot Collaboration in Modular Construction
Document Type
Conference Proceeding
Publication Date
1-1-2025
Abstract
Human-robot collaboration (HRC) holds significant potential to enhance productivity and efficiency in modular construction (MC). While existing studies in construction HRC have predominantly focused on technical advancements, limited attention has been paid to human factors and the cognitive impacts of robots on workers during collaboration. This study addresses this gap through an experimental investigation. A controlled experiment was conducted to compare conditions with and without a collaborative robot (cobot). Work performance metrics (e.g., time efficiency, angular accuracy, and screwing quality) and human factors (e.g., fatigue levels, individual effort, and stress states) were assessed using statistical analysis and self-report questionnaires. Results of work performance indicate that cobot integration significantly increased task completion time (TCT) (Est. = 0.314, t = 5.18, p < 0.001), with variations observed across tasks (p = 0.00452). Results of human factors revealed increased fatigue (mean scores rising from 18.9 to 22.0), mental effort (mean scores rising from 40.2 to 50.1), and distress (mean scores rising from 12.2 to 15.9) under the cobot condition, suggesting additional cognitive demands during collaboration. These findings underscore the importance of addressing task complexity and cognitive challenges when implementing cobots in MC workflows. This research contributes to advancing robotics integration and safeguarding worker well-being in modular construction.
Publication Title
Proceedings of the International Symposium on Automation and Robotics in Construction
ISBN
[9780645832228]
Recommended Citation
Wang, Y.,
Hou, X.,
Xiao, B.,
&
Mueller, S.
(2025).
Understanding Cognitive Impacts of Robots in Worker-Robot Collaboration in Modular Construction.
Proceedings of the International Symposium on Automation and Robotics in Construction, 837-844.
http://doi.org/10.22260/ISARC2025/0109
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/2028