About the Lab

Human behavior has been studied from many perspectives and at many scales. Psychology, sociology, anthropology, and neuroscience each use different methodologies, scope, and evaluation criteria to understand aspects of human behavior. Computer science, and in particular robotics, offers a complementary perspective on the study of human behavior.

Our research focuses on building embodied computational models of human social behavior, especially the developmental progression of early social skills. Our work uses computational modeling and socially interactive robots in three methodological roles to explore questions about social development that are difficult or impossible to assail using methods of other disciplines:

Explore the boundaries of human social abilities by studying human-robot interaction

Social robots operate at the boundary of cognitive categories; they are animate but are not alive, are responsive but are not creative or flexible in their responses, and respond to social cues but cannot maintain a deep social dialog. By systematically varying the behavior of the robot, we can chart the range of human social responses. Furthermore, because the behavior of the machine can be precisely controlled, a robot offers a reliable and repeatable stimulus.

Model social skill development using a robot as an embodied, empirical testbed

Social robots offer a modeling platform that not only can be repeatedly validated and varied but also can include social interactions as part of the modeled environment. By implementing a cognitive theory on a robot, we ensure that the model is grounded in real-world perceptions, accounts for the effects of embodiment, and is appropriately integrated with other perceptual, motor, and cognitive skills.
 

Enhance the diagnosis and therapy of social deficits using socially assistive technology

In our collaborations with the Yale Child Study Center, we have found that robots that sense and respond to social cues provide a quantitative, objective measurement of exactly those social abilities which are deficient in individuals with autism. Furthermore, children with autism show a profound and particular attachment to robots, an effect that we are currently leveraging in therapy sessions.
 

To pursue this research, we must surmount considerable challenges in building interactive robots. These challenges are at the leading edge of a fundamental shift that is occurring in robotics research. Societal needs and economic opportunities are pushing robots out of controlled settings and into our homes, schools, and hospitals. As robots become increasingly integrated into these settings, there is a critical need to engage untrained, naïve users in ways that are comfortable and natural. Our research provides a structured approach to constructing robotic systems that elicit, exploit, and respond to the natural behavior of untrained users.