Modeling Trust in Human-Robot Interaction: A Survey
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Abstract (arXiv)
As the autonomy and capabilities of robotic systems increase, they are expected to play the role of teammates rather than tools and interact with human collaborators in a more realistic manner, creating a more human-like relationship. Given the impact of trust observed in human-robot interaction (HRI), appropriate trust in robotic collaborators is one of the leading factors influencing the performance of human-robot interaction. Team performance can be diminished if people do not trust robots appropriately by disusing or misusing them based on limited experience. Therefore, trust in HRI needs to be calibrated properly, rather than maximized, to let the formation of an appropriate level of trust in human collaborators. For trust calibration in HRI, trust needs to be modeled first. There are many reviews on factors affecting trust in HRI, however, as there are no reviews concentrated on different trust models, in this paper, we review different techniques and methods for trust modeling in HRI. We also present a list of potential directions for further research and some challenges that need to be addressed in future work on human-robot trust modeling.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Nov 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 4; 2025: 1.
12 papers.
- 2024Trust in AI: Progress, Challenges, and Future Directionscited by 35
- 2023A Diachronic Perspective on User Trust in AI under Uncertaintycited by 23
- 2023Learning to Make Adherence-Aware Advicecited by 13
- 2021How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Modelcited by 9
- 2023Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunitiescited by 9
- 2023Utility Theory based Cognitive Modeling in the Application of Robotics: A Surveycited by 3
- 2024Optimizing Delegation in Collaborative Human-AI Hybrid Teamscited by 3
- 2022Explain yourself! Effects of Explanations in Human-Robot Interactioncited by 2
- 2021Moral-Trust Violation vs Performance-Trust Violation by a Robot: Which Hurts More?cited by 1
- 2024Optimizing Risk-averse Human-AI Hybrid Teamscited by 1
- 2025Birds of a Different Feather Flock Together: Exploring Opportunities and Challenges in Animal-Human-Machine Teamingcited by 1
- 2024Predicting Trust Dynamics with Dynamic SEM in Human-AI Cooperationcited by 0
- 2025Birds of a Different Feather Flock Together: Exploring Opportunities and Challenges in Animal-Human-Machine Teaming17 Apr 2025
- 2024Predicting Trust Dynamics with Dynamic SEM in Human-AI Cooperation1 Jul 2024
- 2024Optimizing Risk-averse Human-AI Hybrid Teams13 Mar 2024
- 2024Trust in AI: Progress, Challenges, and Future Directions12 Mar 2024
- 2024Optimizing Delegation in Collaborative Human-AI Hybrid Teams8 Feb 2024
- 2023A Diachronic Perspective on User Trust in AI under Uncertainty20 Oct 2023
- 2023Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities12 Oct 2023
- 2023Learning to Make Adherence-Aware Advice1 Oct 2023
- 2023Utility Theory based Cognitive Modeling in the Application of Robotics: A Survey15 Jun 2023
- 2022Explain yourself! Effects of Explanations in Human-Robot Interaction9 Apr 2022
- 2021Moral-Trust Violation vs Performance-Trust Violation by a Robot: Which Hurts More?9 Oct 2021
- 2021How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model16 May 2021