Martin Saerbeck

Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor

Teaching is inherently a social interaction between teacher and student. Despite this knowledge, many educational tools, such as vocabulary training programs, still model the interaction in a tutoring scenario as unidirectional knowledge transfer rather than a social dialog. Therefore, ongoing research aims to develop virtual agents as more appropriate media in education. Virtual agents can induce the perception of a life-like social interaction partner that communicates through natural modalities such as speech, gestures and emotional expressions. This effect can be additionally enhanced with a physical robotic embodiment. This paper presents the development of social supportive behaviors for a robotic tutor to be used in a language learning application. The effect of these behaviors on the learning performance of students was evaluated. The results support that employing social supportive behavior increases learning efficiency of students.

Perception of affect elicited by robot motion

Nonverbal behaviors serve as a rich source of information in inter human communication. In particular, motion cues can reveal details on a persons current physical and mental state. Research has shown, that people do not only interpret motion cues of humans in these terms, but also the motion of animals and inanimate devices such as robots. In order to successfully integrate mobile robots in domestic environments, designers have therefore to take into account how the device will be perceived by the user. In this study we analyzed the relationship between motion characteristics of a robot and perceived affect. Based on a literature study we selected two motion characteristics, namely acceleration and curvature, which appear to be most influential for how motion is perceived. We systematically varied these motion parameters and recorded participants interpretations in terms of affective content. Our results suggest a strong relation between motion parameters and attribution of affect, while the type of embodiment had no effect. Furthermore, we found that the level of acceleration can be used to predict perceived arousal and that valence information is at least partly encoded in an interaction between acceleration and curvature. These findings are important for the design of behaviors for future autonomous household robots.

Towards a design method for expressive robots

Autonomous robots tend to induce the perception of a personality through their behavior and appearance. It has been suggested that the personality of a robot can be used as a design guideline and as a mental model of the robot. We propose a method to design and evaluate personality and expressions for domestic robots.

A Practical Study on the Design of a User-Interface Robot Application

People are striving for easy, natural interfaces. Robotic user interfaces aim at providing this kind of interface by using human like interaction modalities. However, many applications fail, not because of fundamental problems of addressing social interaction but due to an unbalanced design. In this paper we derive a balancing framework for designing robotic user interfaces that balances four key dimensions: user, application, interface and technology. We investigate applicability of the the framework by means of two experiments. The first experiment demonstrates that violations to the balancing framework can negate the efforts to improve an interface with natural interaction modalities. In the second experiment we present a real world application that adheres to the balancing concepts. Our results show that a balanced design is a key factor for the success or failure of a given robotic interface.