Socially Assistive Robots

Socially assistive robotics (SAR) is a new field of intelligent robotics that focuses on developing machines capable of assisting people through social rather than physical interaction. The robot’s physical embodiment is at the heart of SAR’s effectiveness, as it leverages the inherently human tendency to engage with lifelike (but not necessarily human-like or otherwise biomimetic) social behavior. People readily ascribe intention, personality and emotion to robots; SAR uses engagement resulting from interaction involving gesture, movement, affect and speech to make robots capable of motivating, coaching, and sustaining user activities and improving human learning, training, performance and health outcomes. Human-robot interaction (HRI) for SAR is a growing multifaceted research area at the intersection of engineering, health sciences, neuroscience, social and cognitive sciences. This talk will describe our research into embodiment, modeling and steering social dynamics and long-term user adaptation for SAR. The research will be grounded in projects involving analysis of multi-modal activity data, modeling personality and engagement, formalizing social use of space and non-verbal communication, and personalizing the interaction with the user over a period of months, among others. The presented methods and algorithms will be validated on implemented SAR systems evaluated by human subject cohorts from a variety of user populations, including stroke patients, children with autism spectrum disorder and elderly with Alzheimer’s and other forms of dementia. SAR will be put in the larger context of robotics for automation vs. robotics for augmentation, with a brief discussion of the implications on the future of work.