ZeST: an VLM-based Zero-Shot Traversability Navigation for Unknown Environments
ZeST uses Large Language Models (LLMs) with visual reasoning to predict terrain traversability in real-time for robots in unknown environments. It generates traversability maps by analyzing images and contextual information, allowing robots to navigate safely without direct experience. This framework provides a cost-effective and scalable solution for advanced autonomous navigation.