Which Terrain Is Better? Preference Learning with VLM Prototypes for Off-Road Traversability Ranking

arXiv:2609.23673 · cs.CV, cs.RO · Submitted 2026-09-20 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-09-20

Updated: 2026-09-20

Terminology

• Accuracy — 14× in this paper · explained in 1 episode
• Benchmark — 11× in this paper · explained in 2 episodes
• Adaptation — 10× in this paper · explained in 1 episode
• Distillation — 8× in this paper · explained in 2 episodes
• Foundation Model — 6× in this paper · explained in 3 episodes
• Foundation Models — 5× in this paper · explained in 7 episodes
• Domain Adaptation — 3× in this paper · explained in 5 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Score Function — 1× in this paper · explained in 4 episodes

Sources

• Advancing Off-Road Autonomous Driving: The Large-Scale ORAD-3D Dataset and Comprehensive Benchmarks
• Robot Navigation Using Physically Grounded Vision-Language Models in Outdoor Environments
• Self-Supervised Online Robot-Agnostic Traversability Estimation for Open-World Environments
• AnyTraverse: An off-road traversability framework with VLM and human operator in the loop
• ZeST: an VLM-based Zero-Shot Traversability Navigation for Unknown Environments
• CATNAV: Cached Vision-Language Traversability for Efficient Zero-Shot Robot Navigation
• From General Vision to Reliable Traversability Estimation: Adapting Vision Foundation Models for Unstructured Outdoor Environments
• SAM 2: Segment Anything in Images and Videos
• Qwen3-VL Technical Report
• DINOv3

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