Vincent Grondin

Vincent Grondin

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Expertise: Automatisation d'opérations forestières, vision par ordinateur, simulations

Vincent Grondin is a Ph.D candidate supervised by Prof. Philippe Giguère at Université Laval, and he is a member of Norlab. He graduated with both a certificate in physics and a bachelor in electrical engineering from Université de Sherbrooke. During his bachelor, he was responsible for ensuring the control and simulation of a Hoverbike as a part of a higly-funded third year project. He also completed two internships at the Canadian Space Agency , where he developed a communication prototype with spatial recognition. Additionally, during an internship at the Speech and Audio Research Group Laboratory , he conducted research on the classification of speech and audio by using artificial intelligence (AI).

Currently, his research focuses on environment perception and simulation by employing AI in forests. Here is an example of his most recent project where AI algorithms perform automatic tree detection:


  • M.Sc. en informatique ( Norlab ) - Université Laval (passage accéléré au doctorat), 2020

  • B.Ing. en génie électrique - Université de Sherbrooke, 2018

  • Certificat en physique - Université de Sherbrooke, 2014


Journal Articles

  1. Grondin, V., Fortin, J.-M., Pomerleau, F., & Giguère, P. (2022). Tree Detection and Diameter Estimation Based on Deep Learning. Forestry: An International Journal of Forest Research, 96(2), 264–276.
     Publisher  Bibtex source

Conference Articles

  1. Fortin, J.-M., Gamache, O., Grondin, V., Pomerleau, F., & Giguère, P. (2022). Instance Segmentation for Autonomous Log Grasping in Forestry Operations. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 6064–6071. Finalist for Best Paper Award on Agri-Robotics! Accepted for oral presentation, arXiv preprint arXiv:2203.01902
     Publisher  Bibtex source
  2. 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. Best Robotic Vision Paper Award!
     PDF Publisher  Bibtex source


  1. Grondin, V., Pomerleau, F., & Giguère, P. (2022). Training Deep Learning Algorithms on Synthetic Forest Images for Tree Detection. In ICRA 2022 Workshop - Innovation in Forestry Robotics: Research and Industry Adoption.
     Bibtex source