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
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
Социальные закладки