ScaTE: A Scalable Framework for Self-Supervised Traversability Estimation in Unstructured Environments. (arXiv:2209.06522v1 [cs.RO])

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 vehicles. Actual driving experience can be utilized in a
self-supervised fashion to learn vehicle-specific traversability. However,
existing methods for learning self-supervised traversability are not highly
scalable for learning the traversability of various vehicles. In this work, we
introduce a scalable framework for learning self-supervised traversability,
which can learn the traversability directly from vehicle-terrain interaction
without …

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