Designing Gaze Behavior for Humanlike Robots

Humanlike robots are designed to communicate with people using human verbal and nonverbal language. Social gaze cues play an important role in this communication. Although research in human-robot interaction has shown that people understand these gaze cues and interpret them as valid signals for human communication, whether they can serve as effective communicative mechanisms and lead to significant social and cognitive outcomes in human-robot interaction remains unknown. Furthermore, the theoretical and empirical foundations for how these mechanisms might be designed to work with the human communicative system have not been systematically explored. The research questions that I seek to address in this area are as follows: What are the design variables for social gaze behavior? How do we design gaze behavior for humanlike robots? Can designed behaviors lead to positive, significant social and cognitive outcomes in human-robot interaction such as better learning, stronger affiliation, and active participation in conversations? This dissertation seeks to find answers to these questions by exploring the design space to identify design variables for social gaze, adapting an approach based on modeling human behavior to designing robot behaviors, and evaluating the social and cognitive outcome of designed behaviors in three studies that focus on different functions of social gaze behavior using three robotic platforms, ASIMO, Robovie, and iii