FLINT: Fast Lightweight Inference for Traversability
Navigation in off-road conditions is challenging due to the lack of structure. There is no fixed vocabulary for what is traversable. The traversability depends on both the environment and the embodiment's dynamics. Neither of these two variables can be hand-labeled at scale. Thus, traversability has to be learned by the embodiment's own experience. Modern platforms tend to use multiple sensors to estimate traversability and navigate: RGBD cameras, lidar, radar, IMU, with computationally intensive platforms to run inference on neural networks. Against this trend, we propose FLINT, a lightweight traversability estimator: a 21.6M-parameter backbone, 38\times smaller than a comparable foundat...
| Authors | William Bonilla, Maxime Boisvert, David-Alexandre Poissant et al. |
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| Primary category | cs.RO |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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