Interaction Templates: A Data-Driven Approach for Authoring Robot Programs

Socially interactive robots present numerous unique programming challenges for interaction developers. While modern authoring tools succeed at making the authoring experience approachable and convenient for developers from a wide variety of backgrounds, they do little in the way of targeting assistance to developers based on the specific task or interaction being authored. We propose interaction templates, a data-driven solution for (1) matching in-progress robot programs to candidate task or interaction models and then (2) providing assistance to developers by using the matched models to generate modifications to in-progress programs. In this paper, we present the various different dimensions that define first how interaction templates can be used, then how interaction templates can be represented, and finally how they might be collected.