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Evora: Deep evidential traversability learning for risk-aware off-road autonomy
Traversing terrain with good traction is crucial for achieving fast off-road navigation. Instead
of manually designing costs based on terrain features, existing methods learn terrain …
of manually designing costs based on terrain features, existing methods learn terrain …
Learning off-road terrain traversability with self-supervisions only
Estimating the traversability of terrain should be reliable and accurate in diverse conditions
for autonomous driving in off-road environments. However, learning-based approaches …
for autonomous driving in off-road environments. However, learning-based approaches …
V-strong: Visual self-supervised traversability learning for off-road navigation
Reliable estimation of terrain traversability is critical for the successful deployment of
autonomous systems in wild, outdoor environments. Given the lack of large-scale annotated …
autonomous systems in wild, outdoor environments. Given the lack of large-scale annotated …
Roadrunner-learning traversability estimation for autonomous off-road driving
Autonomous navigation at high speeds in off-road environments necessitates robots to
comprehensively understand their surroundings using onboard sensing only. The extreme …
comprehensively understand their surroundings using onboard sensing only. The extreme …
Scate: A scalable framework for self-supervised traversability estimation in unstructured environments
For the safe and successful navigation of autonomous vehicles in unstructured
environments, the traversability of terrain should vary based on the driving capabilities of the …
environments, the traversability of terrain should vary based on the driving capabilities of the …
Tartandrive 2.0: More modalities and better infrastructure to further self-supervised learning research in off-road driving tasks
We present TartanDrive 2.0, a large-scale off-road driving dataset for self-supervised
learning tasks. In 2021 we released TartanDrive 1.0, which is one of the largest datasets for …
learning tasks. In 2021 we released TartanDrive 1.0, which is one of the largest datasets for …
ForestTrav: 3D LiDAR-only forest traversability estimation for autonomous ground vehicles
Autonomous navigation in unstructured vegetated environments remains an open
challenge. To successfully operate in these settings, autonomous ground vehicles (AGVs) …
challenge. To successfully operate in these settings, autonomous ground vehicles (AGVs) …
Learning-on-the-drive: Self-supervised adaptation of visual offroad traversability models
E Chen, C Ho, M Maulimov, C Wang… - ar** traversability models for off-
road navigation, but these models often struggle with inputs unseen during training. Existing …
road navigation, but these models often struggle with inputs unseen during training. Existing …
Wild visual navigation: Fast traversability learning via pre-trained models and online self-supervision
Natural environments such as forests and grasslands are challenging for robotic navigation
because of the false perception of rigid obstacles from high grass, twigs, or bushes. In this …
because of the false perception of rigid obstacles from high grass, twigs, or bushes. In this …