Expressivity Comes First, Movement Follows: Embodied Interaction as Intrinsically Expressive Driver of Robot Behaviour

Social robotics is concerned with the development of embodied agents that can interact naturally with humans in social contexts. Such agents need to gather information about the interaction in a way similar to that of humans-that is, relying not only on verbal communication but taking into account the expressivity and intentionality of movement and the intonation of speech. It is commonly accepted that expressivity derives from a set of specialized behaviours, which often function as expressions of emotions. In this paper, we advocate for an embodied dynamic interaction approach, arguing that not just certain specialized behaviours are expressive, but rather all embodied interaction, insofar as it creates a relationship with the world, is intrinsically expressive and provides important contextual cues. This non-reductionist approach highlights the importance of movement understanding for emotion and cognition generally. Drawing from emotion theory, we present an interdisciplinary approach that uses dance as an empirical and experiential domain of research naturally concerned with the issue of expressivity beyond paradigmatic expressions. In particular, the Laban system that captures expressivity in dance serves as the foundation for an interaction design of embodied objects, robots in particular, capable of embedding (i.e. performing and understanding) movement expressivity in social interaction. In conclusion, we argue that there are grounds for more research in social robots that base their interactions on dynamical principles, going beyond occasional expressivity.