Lockheed Martin Robotics Seminar Series
Interactive Autonomy: A human-centered approach to learning and control
Department of Computer Science and Electrical Engineering
Today’s society is rapidly advancing towards robotics systems that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes.Formalizing interaction is a crucial component in seamless collaboration and coordination between humans and today's robotics systems.
In this talk, I will first discuss our recent results on efficient and active learning of predictive models of humans' preferences by eliciting comparisons from humans. I will then formalize interactive autonomy, and our approach in design of learning and control algorithms that influence humans in interactive settings. I will further analyze the global implications of human-robot interaction and its societal impacts in the setting of autonomous driving.
Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning and control theory, and algorithmic human-robot interaction. Specifically, she works on developing efficient algorithms for autonomous systems that safely and reliably interact with people. Dorsa has received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) at UC Berkeley in 2017, and has received her bachelor’s degree in EECS at UC Berkeley in 2012. She is awarded the Amazon Faculty Research Award, the NSF and NDSEG graduate research fellowships as well as the Leon O. Chua departmental award departmental award.