Claire J. Tomlin — Lecture
| Event Date: | January 29, 2021 |
|---|---|
| Speaker: | Claire J. Tomlin | Charles A. Desoer Chair in the College of Engineering,
Professor of Electrical Engineering and Computer Sciences |
| Speaker Affiliation: | University of California, Berkeley |
| Time: | 1:00-2:00 p.m. |
| Location: | Zoom |
| Contact Name: | Maria Longoria-Littleton |
| Contact Phone: | +1 765 49-40015 |
| Contact Email: | mlongori@purdue.edu |
| Priority: | Yes |
| School or Program: | College of Engineering |
| College Calendar: | Show |
Safe Learning in Robotics
Abstract:
A great deal of research in recent years has focused on robot learning. In many applications, guarantees that specifications are satisfied throughout the learning process are paramount. For the safety specification, we present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory. In the first part of the talk, we will review these methods and their application to collision avoidance and avionics design in air traffic management systems, and networks of unmanned aerial vehicles. In the second part, we will present a toolbox of methods combining reachability with data-driven techniques inspired by machine learning, to enable performance improvement while maintaining safety. We will illustrate these “safe learning” methods on robotic platforms at Berkeley, including demonstrations of motion planning around people, and navigating in a priori unknown environments.
Biography:
Claire Tomlin is a Professor of Electrical Engineering and Computer Sciences at the University of California at Berkeley, where she holds the Charles A. Desoer Chair in Engineering. Claire received her B.A.Sc. in EE from the University of Waterloo in 1992, her M.Sc. in EE from Imperial College, London, in 1993, and her PhD in EECS from Berkeley in 1998. She held the positions of Assistant, Associate, and Full Professor at Stanford from 1998-2007, and in 2005 joined Berkeley. Claire works in hybrid systems and control, and integrates machine learning methods with control theoretic methods in the field of safe learning. She works in the applications of air traffic and unmanned air vehicle systems. Claire is a MacArthur Foundation Fellow, an IEEE Fellow, and an AIMBE Fellow. She was awarded the Donald P. Eckman Award of the American Automatic Control Council in 2003, an Honorary Doctorate from KTH in 2016, and in 2017 she won the IEEE Transportation Technologies Award. In 2019, she was elected to the National Academy of Engineering and the American Academy of Arts and Sciences.
Hosted by ICON, School of Aeronautics and Astronautics, School of Electrical and Computer Engineering