In the last decade, there has been a major shift in the perception, use and
predicted applications of robots. In contrast to their early industrial
counterparts, robots are envisioned to operate in increasingly complex and
uncertain environments, alongside humans, and over long periods of time.
In my talk, I will argue that machine learning is indispensable in order for
this new generation of robots to achieve high performance. Based on various
examples (and videos) ranging from aerial-vehicle dancing to ground-vehicle
racing, I will demonstrate the effect of robot learning, and highlight how
our learning algorithms intertwine model-based control with machine
learning. In particular, I will focus on our latest work that provides
guarantees during learning (for example, safety and robustness guarantees)
by combining traditional controls methods (nonlinear, robust and model
predictive control) with Gaussian process regression.
Biography: Angela Schoellig is an Assistant Professor at the University of Toronto
Institute for Aerospace Studies (UTIAS) and Associate Director of the Center
for Aerial Robotics Research and Education (CARRE).
With her team, she conducts research at the interface of robotics, controls
and machine learning. Her goal is to enhance the performance, safety and
autonomy of robots by enabling them to learn from past experiments and from
each other. You can watch her robots, both unmanned aerial vehicles (UAVs)
and autonomous ground robots, perform slalom races and flight dances at
She is one of Robohub's "25 women in robotics you need to know about
(2013)", winner of MIT's Enabling Society Tech Competition, finalist of
Dubai's 2015 $1M "Drones for Good" competition, and youngest member of the
2014 Science Leadership Program, which promotes outstanding scientists in
Canada. She has been a keynote speaker at outreach events including
TEDxUofT, Lift China, and the Girls Leadership in Engineering Experience
Angela received her Ph.D. from ETH Zurich (with Prof. Raffaello D'Andrea),
and holds both an M.Sc. in Engineering Science and Mechanics from the
Georgia Institute of Technology (Prof. Magnus Egerstedt) and a Masters
degree in Engineering Cybernetics from the University of Stuttgart, Germany
(Prof. Frank Allgower). Her Ph.D. was awarded the ETH Medal and the 2013
Dimitris N. Chorafas Foundation Award (as one of 35 worldwide).