TY - GEN
T1 - Investigating the Impact of Construction Robots Autonomy Level on Workers’ Cognitive Load
AU - Shayesteh, S.
AU - Jebelli, H.
N1 - Publisher Copyright:
© 2023, Canadian Society for Civil Engineering.
PY - 2023
Y1 - 2023
N2 - Construction robots are being used for several repetitive, basic tasks in construction sites, and soon it is expected that they will be used in more complicated operations to assist human workers. However, given the dynamic and unstructured nature of construction sites, robots’ engagement in complex tasks requires high intelligence and autonomy levels. While working with highly-automated robots in shared workspaces can result in higher productivity and lower costs, it may not be embraced by many construction workers, resulting in poor performance, safety, and well-being. Therefore, it is critical to profoundly understand workers’ response to imminent autonomous robots before their vast implementation at construction sites. In this context, effective measurement of workers’ cognitive load provides insights into human responses to robotic co-workers. Therefore, this study investigates the impact of autonomy levels of construction robots on workers’ cognitive load using qualitative and quantitative methods. To that end, an experiment was conducted in which subjects performed a masonry task in two different scenarios in collaboration with a semi-autonomous and an autonomous robot. An immersive virtual environment was used as a controlled and safe testbed to examine workers’ cognitive load while working alongside a virtual construction robot. Subjects’ electroencephalography (EEG) signals and questionnaires (NASA-TLX) were collected to assess cognitive load during each scenario. The results indicated that subjects’ cognitive load increased with an increase in the robot autonomy level, suggesting incorporating human factors in designing collaborative robots. The findings can help to determine adequate autonomy levels for seamless human–robot collaboration at construction sites.
AB - Construction robots are being used for several repetitive, basic tasks in construction sites, and soon it is expected that they will be used in more complicated operations to assist human workers. However, given the dynamic and unstructured nature of construction sites, robots’ engagement in complex tasks requires high intelligence and autonomy levels. While working with highly-automated robots in shared workspaces can result in higher productivity and lower costs, it may not be embraced by many construction workers, resulting in poor performance, safety, and well-being. Therefore, it is critical to profoundly understand workers’ response to imminent autonomous robots before their vast implementation at construction sites. In this context, effective measurement of workers’ cognitive load provides insights into human responses to robotic co-workers. Therefore, this study investigates the impact of autonomy levels of construction robots on workers’ cognitive load using qualitative and quantitative methods. To that end, an experiment was conducted in which subjects performed a masonry task in two different scenarios in collaboration with a semi-autonomous and an autonomous robot. An immersive virtual environment was used as a controlled and safe testbed to examine workers’ cognitive load while working alongside a virtual construction robot. Subjects’ electroencephalography (EEG) signals and questionnaires (NASA-TLX) were collected to assess cognitive load during each scenario. The results indicated that subjects’ cognitive load increased with an increase in the robot autonomy level, suggesting incorporating human factors in designing collaborative robots. The findings can help to determine adequate autonomy levels for seamless human–robot collaboration at construction sites.
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U2 - 10.1007/978-981-19-0503-2_21
DO - 10.1007/978-981-19-0503-2_21
M3 - Conference contribution
AN - SCOPUS:85131926065
SN - 9789811905025
T3 - Lecture Notes in Civil Engineering
SP - 255
EP - 267
BT - Proceedings of the Canadian Society of Civil Engineering Annual Conference 2021 - CSCE21 General Track Volume 1
A2 - Walbridge, Scott
A2 - Nik-Bakht, Mazdak
A2 - Ng, Kelvin Tsun
A2 - Shome, Manas
A2 - Alam, M. Shahria
A2 - el Damatty, Ashraf
A2 - Lovegrove, Gordon
PB - Springer Science and Business Media Deutschland GmbH
T2 - Annual Conference of the Canadian Society of Civil Engineering, CSCE 2021
Y2 - 26 May 2021 through 29 May 2021
ER -