Ghost-in-the-Machine reveals human social signals for human-robot interaction.

ABSTRACT: We used a new method called "Ghost-in-the-Machine" (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognit

SUBMITTER: Loth S 

PROVIDER: S-EPMC4631814 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature