François Pomerleau made his debut in research by interacting with the Canadian Space Agency and the European Space Agency during his studies in computer engineering at Sherbrooke University. He got his Master’s degree from this university in 2009 after a one-year stay at EPFL, where he worked on an autonomous car prototype. He completed his Ph.D. at ETH Zurich in 2013 during which he participated in several robotic deployments in uncontrolled environments, including work with European fire brigades and in alpine lakes. He received a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada to continue his research at the University of Toronto in mobile robotics. Since September 2017, he is an assistant professor in the Computer Science and Software Engineering Department at Laval University.
He is the director of the Northern Robotics Laboratory (Norlab) and his research interests include 3D reconstruction of environments using laser data, autonomous navigation, search and rescue activities, environmental monitoring, trajectory planning, and scientific methodology applied to robotics. He received three best paper awards related to his contributions to field robotics. He also received the 2022 Early career award from the Canadian society of computer science (CS-Can). François is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), an associate editor for the journal IEEE Robotics and Automation Letters, and the journal Frontiers in Robotics and AI. He also stands on the international committees of the conference "Field and Service Robotics" and the "Conference on Robots and Vision".
The importance of field testing in autonomous vehicle research - Lessons learned from subarctic to subterranean environments
As the promise of autonomous cars keeps being delayed, more and more questions are raised about the accessibility of this technology in remote locations. Moreover, extreme meteorological events are on the rise with the concretization of climate change. This new reality stresses the importance of the robustness of navigation algorithms against harsh environmental conditions.
In an era of simulations and augmented datasets, this presentation will focus on our efforts in facing complex environments through field robotics. Field robotics consists of a sub-community of researchers challenging theoretical simplifications with experimental work closer to real applications. We will give an overview of our latest scientific results with an emphasis on lessons learned related to lidar-based mapping, navigation in subarctic conditions, and subterranean exploration.