Preparing For A Robotic Revolution

Robots do just fine with repetition, but adaptability is key for real-world scenarios. That's where today's robotics research comes in.

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Robotics and automation are already a cornerstone of commercial manufacturing. Predictable environments and repetitive actions make it relatively simple for programmers to teach robots how to behave and perform tasks safely.

In the real world, however, robots will need to be adaptive. Angela Schoellig, assistant professor at the University of Toronto Institute for Aerospace Studies (UTIAS), builds smart robots to extend human capabilities, much like how computers and the internet have changed our daily lives, bringing robots out of the factory and into the real world alongside people.

Schoellig believes that “the biggest challenge that we are addressing is that those robots have to cope with unknown environments, unpredictable situations. Our research is really concerned with enabling them to learn by themselves based on their experience.”

Take, for instance, a self-driving car. Aside from avoiding collisions with pedestrians or other cars, the road and weather conditions are constantly changing. Sunshine and snowfall change the environment drastically. To operate safely, these cars could be programmed to drive very conservatively all the time, but this would not be ideal. With adaptive programming a robotic car could drive conservatively for a few moments while assessing the road, and then follow the program that best suits its current conditions.

Schoellig’s research takes these principles even further, allowing robots to share information and learn from one another, even if those robots are not identical. Her YouTube channel is filled with videos of robots learning and adapting, and even dancing to music as they fly. Her robots can also offload heavy computing onto the cloud, using the power of the internet to help them make decisions.

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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 weekend.

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).