RANGER: Monocular Zero-Shot Semantic Navigation
Published:Dec 30, 2025 13:25
•1 min read
•ArXiv
Analysis
This paper introduces RANGER, a novel zero-shot semantic navigation framework that addresses limitations of existing methods by operating with a monocular camera and demonstrating strong in-context learning (ICL) capability. It eliminates reliance on depth and pose information, making it suitable for real-world scenarios, and leverages short videos for environment adaptation without fine-tuning. The framework's key components and experimental results highlight its competitive performance and superior ICL adaptability.
Key Takeaways
- •Proposes RANGER, a monocular zero-shot semantic navigation framework.
- •Eliminates reliance on depth and pose information.
- •Demonstrates strong in-context learning (ICL) capability.
- •Improves task efficiency by observing short videos of new environments.
- •Achieves competitive performance and superior ICL adaptability.
Reference
“RANGER achieves competitive performance in terms of navigation success rate and exploration efficiency, while showing superior ICL adaptability.”