  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.
