Generating Engagement Behaviors in Human-Robot Interaction

Abstract

Based on a study of the engagement process between humans, I have developed models for four types of connection events involving gesture and speech: directed gaze, mutual facial gaze, adjacency pairs and backchannels. I have developed and validated a reusable Robot Operating System (ROS) module that supports engagement between a human and a humanoid robot by generating appropriate connection events. The module implements policies for adding gaze and pointing gestures to referring phrases (including deictic and anaphoric references), performing end-of-turn gazes, responding to human-initiated connection events and maintaining engagement. The module also provides an abstract interface for receiving information from a collaboration manager using the Behavior Markup Language (BML) and exchanges information with a previously developed engagement recognition module. This thesis also describes a Behavior Markup Language (BML) realizer that has been developed for use in robotic applications. Instead of the existing fixed-timing algorithms used with virtual agents, this realizer uses an event-driven architecture, based on Petri nets, to ensure each behavior is synchronized in the presence of unpredictable variability in robot motor systems. The implementation is robot independent, open-source and uses the Robot Operating System (ROS)