AIC Seminar Series

Recent innovations in crowd computing, crowdsourcing and remote access technologies have altered the way in which many traditional artificial intelligence and robotics studies are designed, conducted and evaluated. Human-Robot Interaction (HRI) research has particularly benefited from the greater access to data and people that such techniques enable, leading to new data-driven techniques and more extensive evaluations. In this talk, I will present three recent projects aimed at enabling robots to learn from everyday people, examining how access to thousands of potential robot users can be leveraged to overcome several challenges of traditional HRI research. I will present a comparison of several leading learning from demonstration algorithms, discuss how "gamification" can assist in data collection for robot learning, and introduce a new web-based framework for rapid prototyping and evaluation of HRI and robot learning techniques.

Sonia Chernova is an Assistant Professor at Worcester Polytechnic Institute (WPI). Her research interests lie in interactive machine learning, adjustable autonomy and human-robot interaction. Her work focuses on the development algorithms that enable robots to learn through social interaction with humans. Prof. Chernova received her Ph.D. from Carnegie Mellon University in 2009 and spent one year as a postdoc at the MIT Media Lab before joining WPI.

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