Socially assistive robotics: Personalized machines that (Provide) care

Abstract

Socially assistive robotics (SAR) is a new subfield of robotics that bridges human-robot interaction (HRI), rehabilitation robotics, social robotics, and service robotics. SAR focuses on developing machines capable of assisting users, typically in health and education contexts, 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 humanlike or otherwise biomimetic) social behavior. This talk will describe 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. 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 Alzheimers and other forms of dementia.