Link for Live Seminar

Link for Recorded seminars – 2022/2023 school year

Abstract: Robots have begun to transition from assembly lines, where they are physically separated from humans, to human-populated environments and human-enhancing applications, where interaction with people is inevitable. With this shift, research in human-robot interaction (HRI) has grown to allow robots to work with and around humans on complex tasks, augment and enhance people, and provide the best support to them. In this talk, I will provide an overview of the work performed in the HIRO Group and our efforts toward intuitive, human-centered technologies for the next generation of robot workers, assistants, and collaborators. More specifically, I will present our research on: a) robots that are safe to people, b) robots that are capable of operating in complex environments, and c) robots that are good teammates. In all, this research will enable capabilities that were not previously possible, and will impact work domains such as manufacturing, construction, logistics, the home, and health care.

Bio: Alessandro Roncone is Assistant Professor in the Computer Science Department at University of Colorado Boulder. He received his B.Sc. summa cum laude in Biomedical Engineering in 2008, and his M.Sc. summa cum laude in NeuroEngineering in 2011 from the University of Genoa, Italy. In 2015 he completed his Ph.D. in Robotics, Cognition and Interaction Technologies from the Italian Institute of Technology [IIT], working on the iCub humanoid in the Robotics, Brain and Cognitive Sciences department and the iCub Facility. From 2015 to 2018, he was Postdoctoral Associate at the Social Robotics Lab in Yale University, performing research in Human-Robot Collaboration for advanced manufacturing. He joined as faculty at CU Boulder in August 2018, where he is director of the Human Interaction and Robotics Group (HIRO, https://hiro-group.ronc.one/ ) and co-director of the Interdisciplinary Research Theme in Engineering Education Research and AI-augmented Learning (EER-AIL IRT,  https://www.colorado.edu/irt/engineering-education-ai/ ).