Simon-Pierre Deschênes

Simon-Pierre Deschênes

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simon-pierre.deschenes.1@ulaval.ca

Expertise: 3D localization and mapping, Iterative Closest Point, registration, robot driver

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Simon-Pierre Deschênes is a PhD student at Norlab, under the supervision of Pr. François Pomerleau. After his internship in the laboratory in summer 2018 as part of his bachelor’s degree, Simon-Pierre was captivated by 3D mapping and decided to continue his graduate studies in this field. His research project is part of the SNOW project and focuses on 3D localization and mapping in harsh winter conditions using the ICP algorithm. The participation of the different project members allowed them to meet and even go beyond the first milestone objectives. Here is a demonstration of the system that has been implemented in the scope of the project:

At last, Simon-Pierre has participated in several other projects since his arrival in the laboratory, including the 2019 christmas video of Norlab, which he directed:

Education

  • Master’s degree in computer science (fast-track to PhD), 2020

  • Bachelor’s degree in software engineering at Laval University, 2019

Publications

Conference Articles

  1. Deschênes, S.-P., Baril, D., Boxan, M., Laconte, J., Giguère, P., & Pomerleau, F. (2024). Saturation-Aware Angular Velocity Estimation: Extending the Robustness of SLAM to Aggressive Motions. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). https://arxiv.org/abs/2310.07844 Submitted
     PDF    Publisher    Bibtex source
  2. 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). https://doi.org/10.1109/CRV52889.2021.00014
     PDF    Publisher    Bibtex source
  3. Baril, D., Grondin, V., Deschenes, S., Laconte, J., Vaidis, M., Kubelka, V., Gallant, A., Giguere, P., & Pomerleau, F. (2020). Evaluation of Skid-Steering Kinematic Models for Subarctic Environments. 2020 17th Conference on Computer and Robot Vision (CRV), 198–205. https://doi.org/10.1109/CRV50864.2020.00034 Best Robotic Vision Paper Award!
     PDF    Publisher    Bibtex source
  4. Laconte, J., Deschênes, S.-P., Labussière, M., & Pomerleau, F. (2019). Lidar Measurement Bias Estimation via Return Waveform Modelling in a Context of 3D Mapping. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
     PDF    Bibtex source