On Grounding Natural Kind Terms in Human-Robot Communication

Our contribution situates Human-Robot Communication, especially the grounding of Natural Kind Terms, in the interface of Artificial Intelligence, Cognitive Psychology,
Philosophy, Robotics and Semantics. We investigate whether a robot can be grounded in the sense favoured in Artificial Intelligence and Philosophy. We thus extend the notion of grounding to social symbol grounding using an interactive
perspective addressing the question how grounding can be achieved in detail in interaction.
For the acquisition of Natural Kind Terms we establish the notions of foundational common ground and foundational grounding in contrast to the established common
ground and grounding. We introduce the robot setting used and provide a deep evaluation of a tutorial dialogue between a user and the robot. We investigate these Human-Robot Communication data from an ethno-methodological and an
"omniscient" perspective (the latter amounting to consideration of automatic speech recognition results) and test whether these perspectives matter for analysing
grounding. We show that the robot has acquired a partial concept of a Natural Kind Term -- represented by statistics over visual object features -- and that this is shared
knowledge, hence the first step of a grounding sequence. Finally, we argue that grounding of robots can be achieved and extended to situated structures of considerable complexity.