About me

I am Damien LaRocque, and I am passionate about robotics, automation, and electronics. During my bachelor's degree in Electrical Engineering, I was actively involved in a robotics student club, which ignited my interest in the field. I went on to complete a master's degree in Computer Science with a specialization in Field Robotics, where my research focused on developing terrain awareness using proprioceptive sensor data. Additionally, I am interested in making AI more sustainable by adapting current state-of-the-art models for edge computing, allowing them to be used with embedded and resource-efficient devices.

Education

Master degree in Computer Science (2020-2024)

I completed a master degree in Computer Science at the Northern Robotics Laboratory at Université Laval, Quebec City, Canada. My thesis, titled "Terrain Analysis using Data from Proprioceptive Sensors on Mobile Robots," explored the relationship between terrain awareness and proprioceptive sensor data from uncrewed ground vehicles.

Bachelor degree in Electrical Engineering (2015-2020)

I earned a bachelor degree in Electrical Engineering from Université de Moncton, Moncton, Canada. During my undergraduate studies, I represented Canada in the Eurobot robotics competition as part of the Groupe de Robotique de l'Université de Moncton (GRUM). With GRUM, I developed computer vision and localization algorithms for fully autonomous robots. These robots had to perform agility tasks and compete against teams from around fifteen countries worldwide.

Publications

A complete publications list is available on the website of the Norlab.

🚧 Publications list in construction 🚧

Here are the BibTeX entries for my publications:

@article{LaRocque2024,
  title         = {{Proprioception Is All You Need: Terrain Classification for Boreal Forests}},
  author        = {Damien LaRocque and William Guimont-Martin and David-Alexandre Duclos and Philippe Giguère and François Pomerleau},
  doi           = {10.48550/arXiv.2403.16877},
  url           = {https://arxiv.org/abs/2403.16877},
  eprint        = {2403.16877},
  archiveprefix = {arXiv},
  journal       = {arXiv preprint arXiv:2403.16877, accepted to the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year          = {2024},
  arxivid       = {2403.16877},
  primaryclass  = {cs.RO}
}

% Coauthorships
@inproceedings{Vaidis2023,
  title     = {Uncertainty Analysis for Accurate Ground Truth Trajectories with Robotic Total Stations},
  url       = {http://dx.doi.org/10.1109/iros55552.2023.10341529},
  doi       = {10.1109/iros55552.2023.10341529},
  booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  publisher = {IEEE},
  author    = {Vaidis,  Maxime and Dubois,  William and Daum,  Effie and LaRocque,  Damien and Pomerleau,  Fran\c{c}ois},
  year      = {2023},
  month     = oct
}

@article{Baril2022,
  title     = {Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned},
  volume    = {2},
  issn      = {2771-3989},
  url       = {http://dx.doi.org/10.55417/fr.2022050},
  doi       = {10.55417/fr.2022050},
  number    = {1},
  journal   = {Field Robotics},
  publisher = {Field Robotics Publication Society},
  author    = {Baril,  Dominic and Desch\^enes,  Simon-Pierre and Gamache,  Olivier and Vaidis,  Maxime and LaRocque,  Damien and Laconte,  Johann and Kubelka,  Vladimír and Giguère,  Philippe and Pomerleau,  Fran\c{c}ois},
  year      = {2022},
  month     = mar,
  pages     = {1628–1660}
}