HUNTER: Highlight the Unexpected with Navigation Through Extreme Regions

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In the 2019 Special Report on the Ocean and Cryosphere in a Changing Climate, the Intergovernmental Panel on Climate Change (IPCC) states that climate change adaptation implies dealing with the uncertainty of increasing extreme meteorological events. Moreover, there is evidence that the decline of the Arctic sea ice led to an increase in heavy snowfall events in the Northern Hemisphere. Finally, improving perception algorithms for autonomous navigation in poor weather conditions is currently an open challenge. Experiments supporting the creation of such algorithms require safe access to an area with a high probability of snowfall, specialized robotic equipment, and large scientific expertise on autonomous navigation that is difficult to find within a single laboratory.The University of Toronto has well-established expertise in state-estimation theory and camera-based navigation solutions for autonomous vehicles. Led by Professor Barfoot, many innovative applications and key scientific publications were achieved in the last two decades by combining complex field deployments of robots and solid theoretical background. In recent years, the laboratory started to investigate the use of radar as a substitute for cameras for localization. Radar has the key advantage of being able to perceive obstacles through heavy snowfall, at the cost of more uncertainty of measurements.Laval University has emerging expertise in autonomous navigation in the cryosphere with the creation of the Northern Robotics Laboratory three years ago. Through strategic infrastructure investments and long-term collaborations with industrial partners, the laboratory, led by professors Pomerleau and Giguère, has access to a large-scale autonomous ground vehicle capable of navigation over deep snow covers. Through key publications and international accolades, François Pomerleau has established expertise in lidar-based navigation algorithms, which complements the co-applicant expertise well. Finally, the university owns a research forest of 250 square kilometres over which six meters of snow are falling every year. This installation is equipped to accommodate researchers for many days and is the centerpiece of this collaborative research program.By combining the strengths of this interprovincial team, this research program aims at validating autonomous navigation solutions for off-road navigation in winter conditions. By combining strong theoretical foundations with experimental evidence based on large-scale field deployments, it will be possible to discover robust algorithms against the large uncertainty that winter conditions produce. Outcomes of this program will augment the international visibility of both institutions on autonomy in harsh weather conditions. Moreover, the expertise will support policymakers for the adoption of autonomous cars on our roads, while augmenting the accessibility of autonomous vehicles to Northern communities.