Led by principal investigator Matthias Scheutz from the Department of Computer Science and five co-PIs—Shuchin Aeron from the Department of Electrical and Computer Engineering, Sergio Fantini from the Department of Biomedical Engineering, Jason Rife from the Department of Mechanical Engineering, Nathan Ward from the Department of Psychology, and JP de Ruiter from both the Departments of Computer Science and Psychology—a Tufts team is working on a new interdisciplinary project to provide scientific and engineering foundations for developing autonomous systems designed to work effectively with humans.
Using novel experimental designs, the researchers will collect datasets in a variety of virtual and physical environments to test the capacity of machine learning algorithms to classify human mental states for the project, titled “Enabling Trusted Human-Like Artificial Teammates.” The data will then be used to develop algorithms for autonomous systems to plan, communicate, and act in mixed human-robot teams while incorporating human needs and expectations into the framework.
Watch a video for more information about human-robot interaction at Tufts.
This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-18-1-0465. Any opinions, finding, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the view of the United States Air Force.