arXiv AI October 16, 2026 By Shreya Gummadi, Mateus V. Gasparino, Gianluca Capezzuto, Marcelo Becker, Girish Chowdhary

ZeST: A VLM-based Zero-Shot Traversability Navigation for Unknown Environments

ZeST is a zero‑shot traversability navigation system that uses a vision‑language model (VLM) to generate stochastic measurements, which are fused into an uncertainty‑aware posterior. By avoiding real‑world data collection, ZeST offers a cost‑effective, scalable solution for predicting terrain traversability. Experiments in indoor and outdoor settings show ZeST achieving 90–100% success rates, outperforming baselines that top 60%.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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