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| license: apache-2.0 | |
| pipeline_tag: robotics | |
| library_name: transformers | |
| base_model: Qwen/Qwen2.5-VL-7B-Instruct | |
| datasets: | |
| - Chrono666/Nav-R2-OVON-CoT-Dataset | |
| tags: | |
| - robotics | |
| - navigation | |
| - object-goal-navigation | |
| - vision-language-model | |
| - qwen | |
| # Nav-$R^2$: Dual-Relation Reasoning for Generalizable Open-Vocabulary Object-Goal Navigation | |
| This repository contains the official implementation of the paper [Nav-$R^2$: Dual-Relation Reasoning for Generalizable Open-Vocabulary Object-Goal Navigation](https://huggingface.co/papers/2512.02400). | |
| Object-goal navigation in open-vocabulary settings requires agents to locate novel objects in unseen environments. Nav-$R^2$ proposes a framework that explicitly models target-environment and environment-action relationships through structured Chain-of-Thought (CoT) reasoning and a Similarity-Aware Memory. This approach enables state-of-the-art performance in localizing unseen objects efficiently while maintaining real-time inference. | |
| For more details on the code, installation, training, and evaluation, please refer to the [GitHub repository](https://github.com/AMAP-EAI/Nav-R2). | |
| ## Overview | |
| <p align="center"> | |
| <img src="https://github.com/AMAP-EAI/Nav-R2/raw/main/figs/title.png" width="100%"> | |
| </p> | |
| <p align="center"> | |
| <img src="https://github.com/AMAP-EAI/Nav-R2/raw/main/figs/teaser.png" width="100%"> | |
| </p> | |
| ### Pipeline and Structure | |
| <p align="center"> | |
| <img src="https://github.com/AMAP-EAI/Nav-R2/raw/main/figs/pipeline.png" width="100%"> | |
| </p> | |
| ### Results on OVON | |
| Here shows the results on OVON dataset. Nav-R2 is trained via **ONLY SFT** receiving **ONLY RGB observations** from **ONLY first-person view**, and achieves the best SR on the val-unseen split. | |
| <p align="center"> | |
| <img src="https://github.com/AMAP-EAI/Nav-R2/raw/main/figs/main-results.png" width="100%"> | |
| </p> | |
| ## Citation | |
| If you find our work helpful or inspiring, please feel free to cite it. | |
| ```bibtex | |
| @article{zhou2025navr2, | |
| title={Nav-R2: Dual-Relation Reasoning for Generalizable Open-Vocabulary Object-Goal Navigation}, | |
| author={Authors names and affiliations will be added after review}, | |
| journal={arXiv preprint arXiv:2512.02400}, | |
| year={2025} | |
| } | |
| ``` |