METAVerse: Meta-Learning Traversability Cost Map for Off-Road Navigation

arXiv:2307.13991v2 Announce Type: replace-cross
Abstract: Autonomous navigation in off-road conditions requires an accurate estimation of terrain traversability. However, traversability estimation in unstructured environments is subject to high uncertainty due to the variability of numerous factors that influence vehicle-terrain interaction. Consequently, it is challenging to obtain a generalizable model that can accurately predict traversability in a variety of environments. This paper presents METAVerse, a meta-learning framework for learning a global model that accurately and reliably predicts terrain traversability across diverse environments. …

abstract arxiv autonomous cost cs.cv cs.lg cs.ro environments influence map meta meta-learning metaverse navigation type uncertainty unstructured