Philippe Babin

Philippe Babin

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Expertise: ICP, Iterative Closest Point, registration, M-estimators, robust optimization

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Philippe Babin is currently employed at Argo AI a self-driving car startup. He got a Bachelor’s Degree in Computer Science Engineering at Université Laval in 2017. Throught his master, he works on improving the robustness of Iterative Closest Point (ICP). His first project explored the effects of outlier filters (such as M-estimator) on ICP. He then worked on the development of LIDAR SLAM algorithm for a forest mapping application.

Education

  • M.Sc. in Computer Science - Université Laval, 2017-2019
  • Bachelor’s Degree in Computer Science Engineering - Distinction Profile - Université Laval, 2013-2017

Publications

Journal Articles

  1. Kubelka, V., Dandurand, P., Babin, P., Giguère, P., & Pomerleau, F. (2020). Radio propagation models for differential GNSS based on dense point clouds. Journal of Field Robotics. https://doi.org/10.1002/rob.21988 Bibtex source

Conference Articles

  1. Dandurand, P., Babin, P., Kubelka, V., Giguère, P., & Pomerleau, F. (2019). Predicting GNSS satellite visibility from dense point clouds. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics. PDF Bibtex source
  2. Babin, P., Dandurand, P., Kubelka, V., Giguère, P., & Pomerleau, F. (2019). Large-scale 3D Mapping of Subarctic Forests. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics. PDF Slides Bibtex source
  3. Babin, P., Giguère, P., & Pomerleau, F. (2019). Analysis of Robust Functions for Registration Algorithms. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). PDF Bibtex source

Miscellaneous

  1. Babin, P., Pomerleau, F., & Giguère, P. (2018). Improving the robustness of registration algorithm in complex environments. Colloque du regroupement FRQNT-REPARTI. Bibtex source