Talking Robotics


Organizers: Patrícia Alves-Oliveira, Silvia Tulli, Miguel Vasco, Joana Campos
contact us: talkingrobotics at gmail dot com — support us: buymeacoffe

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Dr. Tesca Fitzgerald is a Postdoctoral Researcher in the Robotics Institute at Carnegie Mellon University. Her research vision lies at the intersection of Human-Robot Interaction and Cognitive Systems. In her research, she develops algorithms and knowledge representations for robots to learn, adapt, and reuse task knowledge through interaction with a human teacher. In doing so, she applies concepts of social learning and cognition to enable robots to adapt to human environments.

Before joining Carnegie Mellon, Dr. Fitzgerald received her PhD at Georgia Tech, where she was co-advised by Dr. Ashok Goel and Dr. Andrea Thomaz. She completed her undergraduate studies at Portland State University with a B.Sc. in Computer Science. Dr. Fitzgerald is an NSF Graduate Research Fellow (2014), Microsoft Graduate Women Scholar (2014), and IBM Ph.D. Fellow (2017).

Speaker Links: Website-Linkedin


Adaptability is an essential skill in human cognition, enabling us to draw from our extensive, life-long experiences with various objects and tasks in order to address novel problems. To date, most robots do not have this kind of adaptability, and yet, as our expectations of robots’ interactive and assistive capacity grows, it will be increasingly important for them to adapt to unpredictable environments in a similar manner as humans.

In this talk I will describe my approaches to the problem of task transfer, enabling a robot to transfer a known task model to address scenarios containing differences in the objects used, object configurations, and task constraints. The primary contribution of my work is a series of algorithms for deriving and modeling domain-specific task information from structured interaction with a human teacher. In doing so, this work enables the robot to leverage the teacher’s domain knowledge of the task (such as the contextual use of an object or tool) in order to address a range of tasks without requiring extensive exploration or re-training of the task. By enabling a robot to ask for help in addressing unfamiliar problems, my work contributes toward a future of adaptive, collaborative robots.

Papers covered during the talk