Project SNOW (Self-driving Navigation Optimized for Winter), Northern Robotics Laboratory (norlab), Laval University, Quebec City, Quebec, Canada

[Airicist2]

Developer - Northern Robotics Laboratory (norlab) (https://pr.ai/showthread.php?t=23880)

norlab.ulaval.ca/research/snow (https://norlab.ulaval.ca/research/snow)

[Airicist2]

https://youtu.be/NRPxY5jqVVE

Project SNOW - Third milestone

Mar 30, 2022


Project SNOW (Self-driving Navigation Optimized for Winter)

Self-driving cars are expected on our roads soon. In the project SNOW (Self-driving Navigation Optimized for Winter), we focus on the unexplored problem of autonomous driving during winter that still raises reliability concerns. We have the expertise to automatically build 3D maps of the environment while moving through it with robots. We aim at using this knowledge to investigate mapping and control solutions for challenging conditions related to Canadian weather.

Themes for Year 3
1- Harder: Deploying on the Nordic mini-Baja race tracks (EDN)
2- Better: Teach & Repeat framework allowing continuous loops
3- Faster: Lidar-based localization within a control loop at 3.2 m/s
4- Stronger: Real-time localization and mapping with extreme motions

Articles:
Deschênes, S.-P., Baril, D., Kubelka, V., Giguère, P., & Pomerleau, F. (2021).
“Lidar Scan Registration Robust to Extreme Motions”.
2021 18th Conference on Robots and Vision (CRV).
ieeexplore.ieee.org/document/9469459 (https://ieeexplore.ieee.org/document/9469459)

Baril, D., Deschênes, S., Gamache, O., Vaidis, M., LaRocque, D., Laconte, J., Kubelka, V., Giguère, P., & Pomerleau, F. (2021).
“Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned”.
Submitted to the journal of Field Robotics. In arXiv preprint https://arxiv.org/abs/2111.13981