Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Systems and Control pp 1–7Cite as

Trust Models for Human-Robot Interaction and Control

  • Living reference work entry
  • First Online:

Abstract

Trust is the key determinant of human’s acceptance and hence willingness to utilize robots. Improper levels of trust may lead to performance degradation, human overload, and even catastrophic consequences. Therefore, in human-robot interaction (HRI) and robot control with humans-in-the-loop, it is crucial to quantify and analyze trust so as to develop robot motion plans, control algorithms, and autonomous decision aids to enable better human-robot collaboration (HRC). This entry provides an overview of the state-of-the-art trust models. In particular, the focus here is on computational trust models that quantify human trust in robots and capture its dynamic evolution. Four categories of computational trust models are introduced and their respective pros and cons summarized and compared. The utilization of computational trust models in robot motion planning, control, and decision-making is reviewed. Future research directions in trust modeling in HRI and control are also discussed.

This is a preview of subscription content, log in via an institution.

Bibliography

  • Chen M, Nikolaidis S, Soh H, Hsu D, Srinivasa S (2018) Planning with trust for human-robot collaboration. In: Proceedings of the 2018 ACM/IEEE international conference on human-robot interaction, pp 307–315. ACM

    Google Scholar 

  • Desai M (2012) Modeling trust to improve human-robot interaction. Doctoral dissertation, University of Massachusetts Lowell

    Google Scholar 

  • Hancock PA, Billings DR, Schaefer KE, Chen JY, De Visser EJ, Parasuraman R (2011) A meta-analysis of factors affecting trust in human-robot interaction. Hum Factors 53(5):517–527

    Article  Google Scholar 

  • Hu H, Lu R, Zhang Z, Shao J (2016) REPLACE: a reliable trust-based platoon service recommendation scheme in VANET. IEEE Trans Veh Technol 66(2):1786–1797

    Article  Google Scholar 

  • Lee SY (2018) Impact of human like cues on human trust in machines: brain imaging and modeling studies for human-machine interactions. Final Report for AOARD Grant FA2386-14-1-4035

    Google Scholar 

  • Lee J, Moray N (1992) Trust, control strategies and allocation of function in human-machine systems. Ergonomics 35(10):1243–1270

    Article  Google Scholar 

  • Merritt SM, Ilgen DR (2008) Not all trust is created equal: dispositional and history-based trust in human-automation interactions. Hum Factors 50(2): 194–210

    Article  Google Scholar 

  • Nam C, Walker P, Li H, Lewis M, Sycara K (2019) Models of trust in human control of swarms with varied levels of autonomy. IEEE Trans Hum Mach Syst 1–11

    Google Scholar 

  • Jian JY, Bisantz AM, Drury CG (2000) Foundations for an empirically determined scale of trust in automated systems. Int J Cogn Ergon 4(1):53–71

    Article  Google Scholar 

  • Sadrfaridpour B, Wang Y (2017) Collaborative assembly in hybrid manufacturing cells: an integrated framework for human-robot interaction. IEEE Trans Autom Sci Eng 15(3):1178–1192

    Article  Google Scholar 

  • Sadrfaridpour B, Saeidi H, Burke J, Madathil K, Wang Y (2016) Modeling and control of trust in human-robot collaborative manufacturing. In: Robust intelligence and trust in autonomous systems, pp 115–141. Springer, Boston

    Chapter  Google Scholar 

  • Saeidi H, Wagner JR, Wang Y (2017) A mixed-initiative haptic teleoperation strategy for mobile robotic systems based on bidirectional computational trust analysis. IEEE Trans Robot 33(6):1500–1507

    Article  Google Scholar 

  • Spencer DA, Wang Y, Humphrey LR (2016) Trust-based human-robot interaction for multi-robot symbolic motion planning. In: 2016 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 1443–1449. IEEE

    Google Scholar 

  • Teacy WL, Patel J, Jennings NR, Luck M (2006) Travos: trust and reputation in the context of inaccurate information sources. Auton Agent Multi-Agent Syst 12(2):183–198

    Article  Google Scholar 

  • Wang X, Shi Z, Zhang F, Wang Y (2015) Dynamic real-time scheduling for human-agent collaboration systems based on mutual trust. Cyber-Phys Syst 1(2–4):76–90

    Article  Google Scholar 

  • Wang Y, Humphrey LR, Liao Z, Zheng H (2018) Trust-based multi-robot symbolic motion planning with a human-in-the-loop. ACM Trans Interact Intell Syst 8(4):31

    Article  Google Scholar 

  • Wagner AR (2009) The role of trust and relationships in human-robot social interaction. Doctoral dissertation, Georgia Institute of Technology

    Google Scholar 

  • Xu A, Dudek G (2015) OPTIMo: online probabilistic trust inference model for asymmetric human-robot collaborations. In: Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction, pp 221–228. ACM

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Clemson University, Clemson, SC, USA

    Yue Wang

Authors
  1. Yue Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yue Wang .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Technological Leadership Institute, University of Minnesota, Minneapolis, Minnesota, USA

    Tariq Samad

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer-Verlag London Ltd., part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Wang, Y. (2020). Trust Models for Human-Robot Interaction and Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_100121-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_100121-1

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation