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
2024. Unraveling the thread: understanding and addressing sequential failures in human-robot interaction. Frontiers in Robotics and AI 11
Hanheide, Marc, Denise Hebesberger & Tomáš Krajník
2017. Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, ► pp. 341 ff.
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.
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.
Lohan, Katrin S., Karola Pitsch, Katharina J. Rohlfing, Kerstin Fischer, Joe Saunders, Hagen Lehmann, Chrystopher Nehaniv & Britta Wrede
2011. 2011 IEEE International Conference on Development and Learning (ICDL), ► pp. 1 ff.
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