Improving HRI design by applying Systemic Interaction Analysis (SInA)

Manja Lohse | University of Bielefeld, Germany

Marc Hanheide | University of Bielefeld, Germany

Karola Pitsch | University of Bielefeld, Germany

Katharina J. Rohlfing | University of Bielefeld, Germany

Gerhard Sagerer | University of Bielefeld, Germany

Social robots are designed to interact with humans. That is why they need interaction models that take social behaviors into account. These usually influence many of a robot’s abilities simultaneously. Hence, when designing robots that users will want to interact with, all components need to be tested in the system context, with real users and real tasks in real interactions. This requires methods that link the analysis of the robot’s internal computations within and between components (system level) with the interplay between robot and user (interaction level). This article presents Systemic Interaction Analysis (SInA) as an integrated method to (a) derive prototypical courses of interaction based on system and interaction level, (b) identify deviations from these, (c) infer the causes of deviations by analyzing the system’s operational sequences, and (d) improve the robot iteratively by adjusting models and implementations. Keywords: analysis tools, user studies, autonomous robots

Published online: 10 December 2009
https://doi.org/10.1075/is.10.3.03loh

Cited by

Cited by 4 other publications

Gerling, K., D. Hebesberger, C. Dondrup, T. Körtner & M. Hanheide

2016. Robot deployment in long-term care. Zeitschrift für Gerontologie und Geriatrie 49:4 ► pp. 288 ff.

Hanheide, Marc, Denise Hebesberger & Tomáš Krajník

2017. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, ► pp. 341 ff.

Lohan, Katrin S., Karola Pitsch, Katharina J. Rohlfing, Kerstin Fischer, Joe Saunders, Hagen Lehmann, Chrystopher Nehaniv & Britta Wrede

2011. In 2011 IEEE International Conference on Development and Learning (ICDL), ► pp. 1 ff.

Lohan, Katrin S., Katharina J. Rohlfing, Karola Pitsch, Joe Saunders, Hagen Lehmann, Chrystopher L. Nehaniv, Kerstin Fischer & Britta Wrede

2012. Tutor Spotter: Proposing a Feature Set and Evaluating It in a Robotic System. International Journal of Social Robotics 4:2 ► pp. 131 ff.

This list is based on CrossRef data as of 14 september 2021. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.