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Julie Alhosh

juliealhosh@gmail.com
Master's Research - McGill University
Supervisor
David Meger
Research Topics
Deep Learning
Reinforcement Learning
Website
Google Scholar
GitHub

Publications

Tractable Representations for Convergent Approximation of Distributional HJB Equations
Julie Alhosh
Harley Wiltzer
David Meger
2025-03-07
ArXiv (preprint)
arxiv.org
arxiv.org
Tractable Representations for Convergent Approximation of Distributional HJB Equations
Julie Alhosh
Harley Wiltzer
David Meger
2025-03-01
arXiv (published)
doi.org
arxiv.org
Topological mapping for traversability-aware long-range navigation in off-road terrain
Jean-Franccois Tremblay
Julie Alhosh
Louis Petit
Faraz Lotfi
Lara Landauro
David Meger
Autonomous robots navigating in off-road terrain like forests open new opportunities for automation. While off-road navigation has been stud… (see more)ied, existing work often relies on clearly delineated pathways. We present a method allowing for long-range planning, exploration and low-level control in unknown off-trail forest terrain, using vision and GPS only. We represent outdoor terrain with a topological map, which is a set of panoramic snapshots connected with edges containing traversability information. A novel traversability analysis method is demonstrated, predicting the existence of a safe path towards a target in an image. Navigating between nodes is done using goal-conditioned behavior cloning, leveraging the power of a pretrained vision transformer. An exploration planner is presented, efficiently covering an unknown off-road area with unknown traversability using a frontiers-based approach. The approach is successfully deployed to autonomously explore two 400 meters squared forest sites unseen during training, in difficult conditions for navigation.
2024-10-02
ArXiv (preprint)
doi.org
arxiv.org