Analyzing Trust Dynamics in Human–Robot Collaboration through Psychophysiological Responses in an Immersive Virtual Construction EnvironmentSource: Journal of Computing in Civil Engineering:;2024:;Volume ( 038 ):;issue: 004::page 04024017-1DOI: 10.1061/JCCEE5.CPENG-5692Publisher: American Society of Civil Engineers
Abstract: Human–robot collaboration (HRC) has emerged as a promising frontier within the construction industry, offering the potential to enhance productivity, safety, and efficiency. The effectiveness of HRC critically depends on the degree of trust that workers place in their robots, and establishing a seamless level of trust in robots is essential to realize the full benefits of HRC. Despite the extensive exploration of trust dynamics in various industries, there is a notable research gap with regard to trust in construction robots, which possess distinctive characteristics in terms of appearance, capabilities, and interaction compared to robots in other sectors. Therefore, in this study, we analyzed trust dynamics within the context of HRC during construction tasks. Both subjective survey data and objective psychophysiological data—including heart rate variability (HRV), electrodermal activity (EDA), and electroencephalogram (EEG)-based emotional valence and arousal—were employed as human trust measures. We conducted experiments for bricklaying tasks in an immersive virtual construction environment and analyzed multifaceted robot factors—including workspace environment, level of interaction, and robot speed, proximity, and angle of approach—and their relationships with human trust measures using statistical analysis, such as t-test, two-way ANOVA, Spearman’s rank correlation, and moderation analysis. The results indicated that workspace environment and level of interaction were the most significant robot factors affecting human trust. EDA exhibited the most sensitivity to variations in robot factors. It was also observed that the effect of speed, proximity, and angle of approach were also dependent on level of interaction and type of workspace environment. There was a significant positive correlation between proximity and perceived trust. The findings of this study contribute to the optimization of robot design and interaction protocols for construction tasks, fostering greater worker trust, and enhancing project productivity and efficiency.
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contributor author | Hardik Chauhan | |
contributor author | Ali Pakbaz | |
contributor author | Youjin Jang | |
contributor author | Inbae Jeong | |
date accessioned | 2024-12-24T10:17:58Z | |
date available | 2024-12-24T10:17:58Z | |
date copyright | 7/1/2024 12:00:00 AM | |
date issued | 2024 | |
identifier other | JCCEE5.CPENG-5692.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4298657 | |
description abstract | Human–robot collaboration (HRC) has emerged as a promising frontier within the construction industry, offering the potential to enhance productivity, safety, and efficiency. The effectiveness of HRC critically depends on the degree of trust that workers place in their robots, and establishing a seamless level of trust in robots is essential to realize the full benefits of HRC. Despite the extensive exploration of trust dynamics in various industries, there is a notable research gap with regard to trust in construction robots, which possess distinctive characteristics in terms of appearance, capabilities, and interaction compared to robots in other sectors. Therefore, in this study, we analyzed trust dynamics within the context of HRC during construction tasks. Both subjective survey data and objective psychophysiological data—including heart rate variability (HRV), electrodermal activity (EDA), and electroencephalogram (EEG)-based emotional valence and arousal—were employed as human trust measures. We conducted experiments for bricklaying tasks in an immersive virtual construction environment and analyzed multifaceted robot factors—including workspace environment, level of interaction, and robot speed, proximity, and angle of approach—and their relationships with human trust measures using statistical analysis, such as t-test, two-way ANOVA, Spearman’s rank correlation, and moderation analysis. The results indicated that workspace environment and level of interaction were the most significant robot factors affecting human trust. EDA exhibited the most sensitivity to variations in robot factors. It was also observed that the effect of speed, proximity, and angle of approach were also dependent on level of interaction and type of workspace environment. There was a significant positive correlation between proximity and perceived trust. The findings of this study contribute to the optimization of robot design and interaction protocols for construction tasks, fostering greater worker trust, and enhancing project productivity and efficiency. | |
publisher | American Society of Civil Engineers | |
title | Analyzing Trust Dynamics in Human–Robot Collaboration through Psychophysiological Responses in an Immersive Virtual Construction Environment | |
type | Journal Article | |
journal volume | 38 | |
journal issue | 4 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/JCCEE5.CPENG-5692 | |
journal fristpage | 04024017-1 | |
journal lastpage | 04024017-16 | |
page | 16 | |
tree | Journal of Computing in Civil Engineering:;2024:;Volume ( 038 ):;issue: 004 | |
contenttype | Fulltext |