Gone are the days of robots solely operating in isolation, without direct interaction with people. Rather, robots are increasingly being deployed in environments and roles that require complex social interaction with humans. The implementation of human-robot teams continues to increase as technology develops in tandem with the state of human-robot interaction (HRI) research. Trust, a major component of human interaction, is an important facet of HRI. However, the ideas of trust repair and trust violations are understudied in the HRI literature. Trust repair is the activity of rebuilding trust after one party breaks the trust of another. These trust breaks are referred to as trust violations . Just as with humans, trust violations with robots are inevitable; as a result, a clear understanding of the process of HRI trust repair must be developed in order to ensure that a human-robot team can continue to perform well after a trust violation. Previous research on human-automation trust and human-human trust can serve as starting places for exploring trust repair in HRI. Although existing models of human-automation and human-human trust are helpful, they do not account for some of the complexities of building and maintaining trust in unique relationships between humans and robots. The purpose of this article is to provide a foundation for exploring human-robot trust repair by drawing upon prior work in the human-robot, human-automation, and human-human trust literature, concluding with recommendations for advancing this body of work.

Prior research has proposed the use of a Perception by Proxy framework that relies on human perception to support actions of autonomy. Given the importance of human perception, this framework highlights the need to understand how human cognitive abilities factor into the human-robot dynamic. The following paper uses a military reconnaissance task to examine how cognitive abilities interact with the gradual implementation of autonomy in a Perception by Proxy framework (i.e., autonomy to detect; autonomy to support rerouting) to predict three dimensions of sequential performance (i.e., speeded detection; target identification; rerouting). Results showed that, in addition to effects of autonomy and task setting, different individual abilities predicted unique aspects of performance. This highlights the need to broaden consideration of cognitive abilities in HRI.

In this paper we briefly describe teaming heuristics as they are applied to human-human teams, and demonstrate their adaptability to human-robot (HR) teams. We discuss a framework developed from Salas's models on teamwork and team training. As HRI technology moves from tele-operative control methods to teamwork with intelligent robots, it is pertinent to properly integrate knowledge about teams into the development of robotic systems. This should lead to highly effective team systems, and may provide insight into the design of robotic entities and system protocols.