Trust Calibration and Trust Respect: A Method for Building Team Cohesion\n in Human Robot Teams

Abstract

Recent advances in the areas of human-robot interaction (HRI) and robot\nautonomy are changing the world. Today robots are used in a variety of\napplications. People and robots work together in human autonomous teams (HATs)\nto accomplish tasks that, separately, cannot be easily accomplished. Trust\nbetween robots and humans in HATs is vital to task completion and effective\nteam cohesion. For optimal performance and safety of human operators in HRI,\nhuman trust should be adjusted to the actual performance and reliability of the\nrobotic system. The cost of poor trust calibration in HRI, is at a minimum, low\nperformance, and at higher levels it causes human injury or critical task\nfailures. While the role of trust calibration is vital to team cohesion it is\nalso important for a robot to be able to assess whether or not a human is\nexhibiting signs of mistrust due to some other factor such as anger,\ndistraction or frustration. In these situations the robot chooses not to\ncalibrate trust, instead the robot chooses to respect trust. The decision to\nrespect trust is determined by the robots knowledge of whether or not a human\nshould trust the robot based on its actions(successes and failures) and its\nfeedback to the human. We show that the feedback in the form of trust\ncalibration cues(TCCs) can effectively change the trust level in humans. This\ninformation is potentially useful in aiding a robot it its decision to respect\ntrust.\n