Robots, Language, and Environments - (How) Can Agents Work in the Human World?
August 11th, 2020 10:45 am - 11:45 am PT
Cynthia Matuszek
Assistant Professor
University of Maryland, Baltimore County
Website: https://www.csee.umbc.edu/~cmat/
Abstract: As robots and other intelligent, embodied agents move from labs and factories into human spaces, it is becoming progressively more impractical to assume that we as technologists will be able to predetermine the environments, tasks, and human interactions they will need to be able to handle. Letting robots learn from end users via natural language is an intuitive, versatile approach to handling novel situations robustly. Grounded language acquisition is concerned with learning the meaning of language as it applies to the physical world. At the same time, physically embodied agents offer a way to learn to understand natural language in the context of the world to which it refers. In this presentation, I will give an overview of our work on joint statistical models to learn the grounded semantics of natural language describing objects, spaces, and actions, and present recent work on using simulation-to-reality approaches to learn from unconstrained human-robot interactions. Our recent work has focused on treating language and perceptual data as projections of a shared, non-observable embedding, and I will describe several outcomes of this approach, including work on making robotics research more affordable and accessible to groups that are not traditionally involved.
Bio: Dr. Cynthia Matuszek is an assistant professor of computer science and electrical engineering at the University of Maryland, Baltimore County, and the director of UMBC’s Interactive Robotics and Language lab. After working as a researcher on the Cyc project, she received her Ph.D. in computer science and engineering from the University of Washington in 2014, with Drs. Dieter Fox and Luke Zettlemoyer. Her research is focused on how robots can learn grounded language from interactions with non-specialists, which includes work in not only robotics, but human-robot interactions, natural language, machine learning, machine bias, and collaborative robot learning, informed by her extensive background in common-sense reasoning and classical artificial intelligence. Dr Matuszek has published in machine learning, artificial intelligence, robotics, and human-robot interaction venues, and was named in the most recent IEEE bi-annual “10 to watch in AI.”