Wild Visual Navigation: Fast Traversability Learning via Pre-Trained Models and Online Self-Supervision

arXiv:2404.07110v1 Announce Type: cross
Abstract: 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 work, we present Wild Visual Navigation (WVN), an online self-supervised learning system for visual traversability estimation. The system is able to continuously adapt from a short human demonstration in the field, only using onboard sensing and computing. One of the key ideas to achieve this is the …

arxiv cs.cv cs.lg cs.ro navigation pre-trained models supervision type via visual visual navigation