Characterization of Human Trust in Robot through Multimodal Physical and Physiological Biometrics in Human-Robot Partnerships

Trust is an attribute that many people use daily, whether consciously thinking of it or not. Although commonly designated as a firm belief in reliability, trust is more complex than many think. It is not just physical, but rather an emotion, feeling, or choice that has many layers, and can be influe...

Full description

Saved in:
Bibliographic Details
Published inIEEE International Conference on Automation Science and Engineering (CASE) pp. 2901 - 2906
Main Authors Parron, Jesse, Li, Rui, Wang, Weitian, Zhou, Mengchu
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.08.2024
Subjects
Online AccessGet full text
ISSN2161-8089
DOI10.1109/CASE59546.2024.10711764

Cover

Abstract Trust is an attribute that many people use daily, whether consciously thinking of it or not. Although commonly designated as a firm belief in reliability, trust is more complex than many think. It is not just physical, but rather an emotion, feeling, or choice that has many layers, and can be influenced in a variety of ways. As robotics and artificial intelligence grow, humans have to deliberate whether they trust working with these technical counterparts or not. In this work, we build computational models to quantitatively characterize and analyze humans' trust in robots using multimodal physical and physiological biometric data based on the TrustBase we have created through user studies in human-robot collaborative tasks. During human-robot collaborative processes, we have collected physical and physiological attribute data of human subjects as well as the users' trust levels for each interaction. This data is used to develop a database known as TrustBase. With the data from TrustBase, computational and analytical approaches are used to investigate the correlation between robot performance factors and humans' trust levels and to characterize humans' trust in robots during human-robot collaboration. Results and their analysis suggest the effectiveness of the developed models, providing new findings to the human factors and cognitive ergonomics in human-robot interaction. Future research directions are also discussed.
AbstractList Trust is an attribute that many people use daily, whether consciously thinking of it or not. Although commonly designated as a firm belief in reliability, trust is more complex than many think. It is not just physical, but rather an emotion, feeling, or choice that has many layers, and can be influenced in a variety of ways. As robotics and artificial intelligence grow, humans have to deliberate whether they trust working with these technical counterparts or not. In this work, we build computational models to quantitatively characterize and analyze humans' trust in robots using multimodal physical and physiological biometric data based on the TrustBase we have created through user studies in human-robot collaborative tasks. During human-robot collaborative processes, we have collected physical and physiological attribute data of human subjects as well as the users' trust levels for each interaction. This data is used to develop a database known as TrustBase. With the data from TrustBase, computational and analytical approaches are used to investigate the correlation between robot performance factors and humans' trust levels and to characterize humans' trust in robots during human-robot collaboration. Results and their analysis suggest the effectiveness of the developed models, providing new findings to the human factors and cognitive ergonomics in human-robot interaction. Future research directions are also discussed.
Author Wang, Weitian
Zhou, Mengchu
Parron, Jesse
Li, Rui
Author_xml – sequence: 1
  givenname: Jesse
  surname: Parron
  fullname: Parron, Jesse
  organization: Montclair State University,School of Computing,Montclair,NJ,USA,07043
– sequence: 2
  givenname: Rui
  surname: Li
  fullname: Li, Rui
  organization: Montclair State University,School of Computing,Montclair,NJ,USA,07043
– sequence: 3
  givenname: Weitian
  surname: Wang
  fullname: Wang, Weitian
  email: wangw@montclair.edu
  organization: Montclair State University,School of Computing,Montclair,NJ,USA,07043
– sequence: 4
  givenname: Mengchu
  surname: Zhou
  fullname: Zhou, Mengchu
  organization: New Jersey Institute of Technology,Department of Electrical and Computer Engineering,Newark,NJ,USA,07102
BookMark eNo1kMlOwzAURQ0Cibb0D5DwDyT4xRnsZYkKRSqigrKuXhKnMUriynYWReLf6QCrOyyOdO-YXPWmV4TcAwsBmHzIZx_zRCZxGkYsikNgGUCWxhdkKjMpeMJ4IhLgl2QUQQqBYELekLFzX4ylTACMyE_eoMXSK6u_0WvTU1PTxdBhT9d2cJ7qnr6bwnjqG2uGbUNfh9brzlTY0lWzd7o8GOyrczCt2Z6aR2065a0u3ZFwAgZnzgqt75V1jd65W3JdY-vU9E8n5PNpvs4XwfLt-SWfLQN9mOODRNQJTwtUgjOhIiihRqyiGopKQlmiiioBmeIVY_I4nFV1EWN8fANlLRmfkLszVyulNjurO7T7zf9d_Bcqy2Q2
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CASE59546.2024.10711764
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Xplore
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISBN 9798350358513
EISSN 2161-8089
EndPage 2906
ExternalDocumentID 10711764
Genre orig-research
GroupedDBID 6IE
6IF
6IH
6IK
6IL
6IN
AAJGR
AAWTH
ACGFS
ADZIZ
AKRWK
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IPLJI
M43
OCL
RIE
RIL
ID FETCH-LOGICAL-i176t-58f536bae8308e21c1faad2f1bd91ccae2d817e3d00997980dfb4a40711a9f903
IEDL.DBID RIE
IngestDate Wed Aug 27 02:16:03 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i176t-58f536bae8308e21c1faad2f1bd91ccae2d817e3d00997980dfb4a40711a9f903
PageCount 6
ParticipantIDs ieee_primary_10711764
PublicationCentury 2000
PublicationDate 2024-Aug.-28
PublicationDateYYYYMMDD 2024-08-28
PublicationDate_xml – month: 08
  year: 2024
  text: 2024-Aug.-28
  day: 28
PublicationDecade 2020
PublicationTitle IEEE International Conference on Automation Science and Engineering (CASE)
PublicationTitleAbbrev CASE
PublicationYear 2024
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0060811
Score 1.8918592
Snippet Trust is an attribute that many people use daily, whether consciously thinking of it or not. Although commonly designated as a firm belief in reliability,...
SourceID ieee
SourceType Publisher
StartPage 2901
SubjectTerms Analytical models
Biological system modeling
Biometrics
Collaboration
Computational modeling
Human factors
Human-robot interaction
Physiology
Reliability engineering
Robots
Title Characterization of Human Trust in Robot through Multimodal Physical and Physiological Biometrics in Human-Robot Partnerships
URI https://ieeexplore.ieee.org/document/10711764
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3NS8MwFA9uJ734NfGbHLy2Nm3SJEcdG0NwDN1gt5FPGGorrrsI_u8maTs_QPDWFPra5L3kJa-_33sAXHFMMLLSGW9mAyUnixhPWCSYIplQWNjUk5Pvx_lohu_mZN6Q1QMXxhgTwGcm9pfhX74u1dqHytwMpwjRHHdAh7K8Jmu1y27ufBtqAFwo4df9m8cB4QR7GEKK4_bRH0VUgg8Z7oJx-_YaOvIUrysZq_dfiRn__Xl7oPdF14OTjSPaB1umOAA73zINHoKP_iYxc827hKWFIYAPp551AZcFfChlWcGmcA8MzNyXUotnOGl0CUWh60a7YsJbz973Sf5XXkIQGNVyJs4mixokveqB2XAw7Y-ipvJCtHQdqCLCLMlyKQzLEmZSpJAVQqcWSc2R07lJNUPUZNpvMClnibYSC382RIJbnmRHoFuUhTkGMGVaW2O5JppiQaVQkmpM3TFGGUSUPgE9P5KL1zq5xqIdxNM_7p-Bba9QH9ZN2TnoVm9rc-H2BZW8DPbwCUMTuwk
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3NT8MgFCc6D-rFrxm_5eC1tbQw4KjLlqnbsuiWeFugQLKorXHdxcT_XaDt_EhMvJUmfS28Bw9ef7_3ALjgmGBkpDXexHhKThIwHrFAsJQkIsXCxI6cPBi2ehN8-0geK7K658JorT34TIfu0v_LV3m6cKEyO8MpQrSFV8EawRiTkq5VL7wt691QBeFCEb9sXz10CCfYARFiHNYP_yij4r1IdwsM6_eX4JGncFHIMH3_lZrx3x-4DZpfhD04WrqiHbCis12w-S3X4B74aC9TM5fMS5gb6EP4cOx4F3CWwftc5gWsSvdAz819yZV4hqNKm1BkqmzUaya8dvx9l-Z_7iR4gUEpZ2StMith0vMmmHQ743YvqGovBDPbgSIgzJCkJYVmScR0jFJkhFCxQVJxZLWuY8UQ1YlyW0zKWaSMxMKdDpHghkfJPmhkeaYPAIyZUkYbroiiWFApUkkVpvYgk2pEUnUImm4kp69leo1pPYhHf9w_B-u98aA_7d8M747BhlOuC_LG7AQ0ireFPrW7hEKeedv4BDTyvlY
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=IEEE+International+Conference+on+Automation+Science+and+Engineering+%28CASE%29&rft.atitle=Characterization+of+Human+Trust+in+Robot+through+Multimodal+Physical+and+Physiological+Biometrics+in+Human-Robot+Partnerships&rft.au=Parron%2C+Jesse&rft.au=Li%2C+Rui&rft.au=Wang%2C+Weitian&rft.au=Zhou%2C+Mengchu&rft.date=2024-08-28&rft.pub=IEEE&rft.eissn=2161-8089&rft.spage=2901&rft.epage=2906&rft_id=info:doi/10.1109%2FCASE59546.2024.10711764&rft.externalDocID=10711764