Topological mapping for traversability-aware long-range navigation in off-road terrain
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909333215772672 |
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| author | Tremblay, Jean-François Alhosh, Julie Petit, Louis Lotfi, Faraz Landauro, Lara Meger, David |
| author_facet | Tremblay, Jean-François Alhosh, Julie Petit, Louis Lotfi, Faraz Landauro, Lara Meger, David |
| contents | Autonomous robots navigating in off-road terrain like forests open new opportunities for automation. While off-road navigation has been studied, 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_01925 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Topological mapping for traversability-aware long-range navigation in off-road terrain Tremblay, Jean-François Alhosh, Julie Petit, Louis Lotfi, Faraz Landauro, Lara Meger, David Robotics Autonomous robots navigating in off-road terrain like forests open new opportunities for automation. While off-road navigation has been studied, 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. |
| title | Topological mapping for traversability-aware long-range navigation in off-road terrain |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.01925 |