Abstract
Human–robot interactions are often affected by error situations that are caused by either the robot or the human. Therefore, robots would profit from the ability to recognize when error situations occur. We investigated the verbal and non-verbal social signals that humans show when error situations occur in human–robot interaction experiments. For that, we analyzed 201 videos of five human–robot interaction user studies with varying tasks from four independent projects. The analysis shows that there are two types of error situations: social norm violations and technical failures. Social norm violations are situations in which the robot does not adhere to the underlying social script of the interaction. Technical failures are caused by technical shortcomings of the robot. The results of the video analysis show that the study participants use many head movements and very few gestures, but they often smile, when in an error situation with the robot. Another result is that the participants sometimes stop moving at the beginning of error situations. We also found that the participants talked more in the case of social norm violations and less during technical failures. Finally, the participants use fewer non-verbal social signals (for example smiling, nodding, and head shaking), when they are interacting with the robot alone and no experimenter or other human is present. The results suggest that participants do not see the robot as a social interaction partner with comparable communication skills. Our findings have implications for builders and evaluators of human–robot interaction systems. The builders need to consider including modules for recognition and classification of head movements to the robot input channels. The evaluators need to make sure that the presence of an experimenter does not skew the results of their user studies.
Highlights
The interaction between humans and robots is often affected by problems that occur during such interactions
In the category head movements we found that participants often look back and forth between robot and experimenter or a group member if present
We subdivided the speech utterances into taskrelated sentences, sentences that the study participants said to the robot to move the given task forward, statements that participants made to comment on the situation to either the robot or another human, questions that participants asked to the robot or a human, audible laughter, and other utterances, for example attempts to speak or hesitation sounds
Summary
The interaction between humans and robots is often affected by problems that occur during such interactions. Human users interact with robots based on their mental models, expectations, and previous experiences. Their expectations are violated and they do not know how to react. In the worst case, such problems can even result in a termination of the interaction (Scheutz et al, 2011). An interruption of the interaction may be caused by the human, for example, if the human interaction partner wants to perform a task that is not within the capability of the robot. Irrespective of the origin, the human interaction partner gets confused and the continuation of the interaction is at stake
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