Capturing Expertise: Developing Interaction Content for a Robot Through Teleoperation by Domain Experts

Abstract

The development of humanlike service robots which interact socially raises a new question: how can we create good interaction content for such robots? Domain experts specializing in the target service have the knowledge for making such content. Yet, while they can easily engage in good face-to-face interactions, we found it difficult for them to prepare conversational content for a robot in written form. Instead, we propose involving experts as teleoperators in a short-cycle iterative development process in which the expert develops content, teleoperates a robot using that content, and then revises the content based on that interaction. We propose a software system and design guidelines to enable such an iterative design process. To validate these solutions, we conducted a comparison experiment in the field, with a teleoperated robot acting as a guide at a tourist information center in Nara, Japan. The results showed that our system and guidelines enabled domain experts with no robotics background to create better interaction content and conduct better interactions than domain experts without our system.