# Modeling Trust in Human-Robot Interaction: A Survey

arXiv: https://arxiv.org/abs/2011.04796 · HTML: https://mlsanity.com/paper/2011.04796/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Nov 2020.

## Built on by (most cited first, 12 of 12)

- [Trust in AI: Progress, Challenges, and Future Directions](https://mlsanity.com/paper/2403.14680/) (2024)
- [A Diachronic Perspective on User Trust in AI under Uncertainty](https://mlsanity.com/paper/2310.13544/) (2023)
- [Learning to Make Adherence-Aware Advice](https://mlsanity.com/paper/2310.00817/) (2023)
- [How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model](https://mlsanity.com/paper/2105.07443/) (2021)
- [Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities](https://mlsanity.com/paper/2310.08565/) (2023)
- [Utility Theory based Cognitive Modeling in the Application of Robotics: A Survey](https://mlsanity.com/paper/2306.09445/) (2023)
- [Optimizing Delegation in Collaborative Human-AI Hybrid Teams](https://mlsanity.com/paper/2402.05605/) (2024)
- [Explain yourself! Effects of Explanations in Human-Robot Interaction](https://mlsanity.com/paper/2204.04501/) (2022)
- [Moral-Trust Violation vs Performance-Trust Violation by a Robot: Which Hurts More?](https://mlsanity.com/paper/2110.04418/) (2021)
- [Optimizing Risk-averse Human-AI Hybrid Teams](https://mlsanity.com/paper/2403.08386/) (2024)
- [Birds of a Different Feather Flock Together: Exploring Opportunities and Challenges in Animal-Human-Machine Teaming](https://mlsanity.com/paper/2504.13973/) (2025)
- [Predicting Trust Dynamics with Dynamic SEM in Human-AI Cooperation](https://mlsanity.com/paper/2407.01752/) (2024)

## 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.