For individuals with motor impairments, assistive robotic manipulators can help them perform daily activities such as pick-and-place tasks, opening doors, pushing buttons, eating, and even personal hygiene. As such, these robotic devices have the potential to allow such individuals to regain some independence in performing these tasks. However, human interaction with these manipulators can often be very challenging.
In this talk, Maria Kyrarini will describe a robot learning framework that empowers a robotic device to automatically generate a sequence of actions from unstructured spoken language, along with the preliminary results from her recent study with 35 participants to evaluate this framework. She will also present the preliminary results from her recent grant from the National Science Foundation (NSF) on developing a personalized assistive robotic system that assesses cognitive fatigue in persons with paralysis.
Maria Kyrarini is an assistant professor of electrical and computer engineering and David Packard Jr. Faculty Fellow at Santa Clara University (SCU). She also leads the Human-Machine Interaction & Innovation (HMI 2 ) Research Group which has been supported by federal (NSF) and SCU internal grants. Her primary research interests are in the fields of Robot Learning from Human Demonstrations, Human-Robot Interaction, and Assistive Robotics with a special focus on enhancing Human Performance.
Prior to SCU, she was a postdoctoral research fellow at the University of Texas at Arlington, and the assistant director of the Heracleia Human-Centered Computing Lab. In 2019, Dr. Kyrarini received her Ph.D. in engineering from the University of Bremen under the supervision of Professor Axel Gräser. The title of her Ph.D. thesis is: “Robot learning from human demonstrations for human-robot synergy”. Before that, she received a master’s in electrical and computer engineering and a master’s in automation systems, both from the National Technical University of Athens (NTUA) in 2012 and 2014, respectively.