Data Driven Non-Verbal Behavior Generation for Humanoid Robots

Abstract

Social robots need non-verbal behavior to make an interaction pleasant and efficient. Most of the models for generating non-verbal behavior are rule-based and hence can produce a limited set of motions and are tuned to a particular scenario. In contrast, data-driven systems are flexible and easily adjustable. Hence we aim to learn a data-driven model for generating non-verbal behavior (in a form of a 3D motion sequence) for humanoid robots.