TY - GEN
T1 - Development of A Multimodal Trust Database in Human-Robot Collaborative Contexts
AU - Parron, Jesse
AU - Nguyen, Thai Thao
AU - Wang, Weitian
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Robots are gradually being incorporated into the workforce to assist with labor-intensive and repetitive tasks, especially in smart manufacturing contexts. This leads to increased human-robot collaboration, which may be an unfamiliar, distrustful, and uncomfortable situation for inexperienced people to navigate. Motivated by these issues and aiming to have a comprehensive understanding of the factors that affect people's trust in robots, we developed a new trust database by investigating the trust between human collaborators wearing four biological sensors and a robot performing collaborative tasks. Using these sensors, we collected trust-related physiological human factors from the brain (EEG), heart (ECG), forearm (EMG), and eyes during human-robot collaborative tasks. As well as a trust rating through a questionnaire, this allows for the creation of a multimodal human-robot trust database (TrustBase). TrustBase provides insightful guidance to optimize and improve the environment deployment and robot configuration in human-robot partnerships within smart manufacturing contexts.
AB - Robots are gradually being incorporated into the workforce to assist with labor-intensive and repetitive tasks, especially in smart manufacturing contexts. This leads to increased human-robot collaboration, which may be an unfamiliar, distrustful, and uncomfortable situation for inexperienced people to navigate. Motivated by these issues and aiming to have a comprehensive understanding of the factors that affect people's trust in robots, we developed a new trust database by investigating the trust between human collaborators wearing four biological sensors and a robot performing collaborative tasks. Using these sensors, we collected trust-related physiological human factors from the brain (EEG), heart (ECG), forearm (EMG), and eyes during human-robot collaborative tasks. As well as a trust rating through a questionnaire, this allows for the creation of a multimodal human-robot trust database (TrustBase). TrustBase provides insightful guidance to optimize and improve the environment deployment and robot configuration in human-robot partnerships within smart manufacturing contexts.
KW - Trust
KW - database.
KW - human factors
KW - physiological signals
KW - robotics
UR - https://www.scopus.com/pages/publications/85179756158
U2 - 10.1109/UEMCON59035.2023.10316014
DO - 10.1109/UEMCON59035.2023.10316014
M3 - Conference contribution
AN - SCOPUS:85179756158
T3 - 2023 IEEE 14th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023
SP - 601
EP - 605
BT - 2023 IEEE 14th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023
A2 - Chakrabarti, Satyajit
A2 - Paul, Rajashree
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023
Y2 - 12 October 2023 through 14 October 2023
ER -