CONF chavarriaga:hri08:2008/IDIAP A Comparative Psychophysical and EEG Study of Different Feedback Modalities for HRI Perrin, Xavier Chavarriaga, Ricardo Ray, Céline Siegwart, Roland Millán, José del R. EXTERNAL https://publications.idiap.ch/attachments/papers/2008/chavarriaga-hri08-2008.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/chavarriaga:rr07-78 Related documents 3rd ACM/IEEE Conf on Human-Robot Interaction (HRI08) 2008 IDIAP-RR 07-78 This paper presents a comparison between six different ways to convey navigational information provided by a robot to a human. Visual, auditory, and tactile feedback mo\-da\-li\-ties were selected and designed to suggest a direction of travel to a human user, who can then decide if he agrees or not with the robot's proposition. This work builds upon a previous research on a novel semi-autonomous navigation system in which the human supervises an autonomous system, providing corrective monitoring signals whenever necessary.We recorded both qualitative (user impressions based on selected criteria and ranking of their feelings) and quantitative (response time and accuracy) information regarding different types of feedback. In addition, a preliminary analysis of the influence of the different types of feedback on brain activity is also shown. The result of this study may provide guidelines for the design of such a human-robot interaction system, depending on both the task and the human user. REPORT chavarriaga:rr07-78/IDIAP A Comparative Psychophysical and EEG Study of Different Feedback Modalities for HRI Perrin, Xavier Chavarriaga, Ricardo Ray, Céline Siegwart, Roland Millán, José del R. EXTERNAL https://publications.idiap.ch/attachments/reports/2007/chavarriaga-idiap-rr-07-78.pdf PUBLIC Idiap-RR-78-2007 2007 IDIAP This paper presents a comparison between six different ways to convey navigational information provided by a robot to a human. Visual, auditory, and tactile feedback mo\-da\-li\-ties were selected and designed to suggest a direction of travel to a human user, who can then decide if he agrees or not with the robot's proposition. This work builds upon a previous research on a novel semi-autonomous navigation system in which the human supervises an autonomous system, providing corrective monitoring signals whenever necessary.We recorded both qualitative (user impressions based on selected criteria and ranking of their feelings) and quantitative (response time and accuracy) information regarding different types of feedback. In addition, a preliminary analysis of the influence of the different types of feedback on brain activity is also shown. The result of this study may provide guidelines for the design of such a human-robot interaction system, depending on both the task and the human user.