Self-driving cars are closer than ever to everyday use, but unpredictable weather is a major roadblock. From degraded senor inputs to machine learning challenges, these cars struggle to keep up with the ever-changing conditions of the road.
Imagine if self-driving cars could operate safely anywhere, no matter the weather.
Join Professor Steven Waslander as he dives into his research aimed at preparing autonomous vehicles for the toughest elements. Discover how his team is advancing perception in adverse weather and developing neural networks that can predict their own limitations. This “self-awareness” is key to smarter, safer decisions and real-world adaptability.
Don’t miss this glimpse into the future of weather-ready autonomous vehicles!
By registering for the Skule™ Lunch & Learn event, you could potentially earn Continuing Professional Development (CPD) credits. CPDs are essential for professional engineers and limited license holders to renew their licenses annually through the PEO PEAK Program.
About the speaker: Professor Steven Waslander
Professor Steven Waslander is the director of the Toronto Robotics and Artifical Intelligence Laboratory (TRAILab) at the Institute for Aerospace Studies in the Faculty of Applied Science and Engineering. He is a recognized expert in autonomous aerial and ground vehicles, specializing in multirotor drones and self-driving cars. With degrees in Aeronautics and Astronautics from Queen’s and Stanford, he founded the Stanford Testbed of Autonomous Rotorcraft (STARMAC) and later the Waterloo Autonomous Vehicle Laboratory (WAVELab), advancing localization, mapping and multi-robot coordination. Currently at the TRAILab his research focuses on robust perception for autonomous driving and SLAM with dynamic camera clusters. His work on autonomous driving, including Canada’s first university-based self-driving vehicle, the Autonomoose, has received awards and media recognition across Canada.
