README.md

---
language:
- en
tags:
- multimodal
- active-perception
- embodied-ai
- robotics
- tactile
- audio
- force
- qwen2.5-omni
pretty_name: ROMA
---

<p align="center">
  <img src="https://raw.githubusercontent.com/GeWu-Lab/ROMA/main/assest/logo.png" width="200" alt="ROMA logo">
</p>

<h1 align="center">ROMA: LLM System for Real-World Object-Centric<br>Multi-Sensory Active Perception</h1>

<h3 align="center"><em>I saw. I touched. I understood.</em></h3>

<p align="center">
  <a href="https://gewu-lab.github.io/ROMA/"><img src="https://img.shields.io/badge/Project-Page-blue" alt="Project Page"></a>
  <a href="https://github.com/GeWu-Lab/ROMA"><img src="https://img.shields.io/badge/Code-GitHub-black" alt="Code"></a>
</p>

<p align="center">
  <a href="https://xxuan01.github.io/">Ruoxuan Feng</a><sup>*</sup>, <a href="https://gitagitty.github.io/">Yutong Chen</a><sup>*</sup>, <a href="https://scholar.google.com.hk/citations?user=v5LctN8AAAAJ">Ruihua Song</a>, <a href="https://hyang0511.github.io/">Huan Yang</a>, <a href="https://www.wangzhongyuan.com/">Zhongyuan Wang</a>, <a href="https://scholar.google.com/citations?user=FLkv_vIAAAAJ">Guocai Yao</a>, <a href="https://dtaoo.github.io/">Di Hu</a><sup>&#9993;</sup>
  <br>
  <sup>*</sup>Equal contribution &nbsp; <sup>&#9993;</sup>Corresponding author
</p>

---

This repository hosts the **checkpoint** and **dataset** of [ROMA](https://github.com/GeWu-Lab/ROMA), an LLM-based system for Real-World Object-Centric Multi-Sensory Active Perception. ROMA integrates vision, audio, touch, and force into a *reasoning-interaction-feedback* loop: the LLM identifies the missing evidence and selects the target object, the interaction (`lift`, `press`, `collide`, `shake`, `rotate`, `squeeze`), and the sensory modalities, while a physical interface executes the interaction and returns the multi-sensory feedback.

<p align="center">
  <img src="https://raw.githubusercontent.com/GeWu-Lab/ROMA/main/assest/teaser.png" width="90%" alt="ROMA teaser">
</p>

## What's Inside

| Component | Description | Status |
| :--- | :--- | :---: |
| **ROMA-7B checkpoint** | Multi-sensory LLM built on [Qwen2.5-Omni](https://github.com/QwenLM/Qwen2.5-Omni) with action / modality tokens, an audio branch, and an [AnyTouch 2](https://github.com/GeWu-Lab/AnyTouch2) tactile branch, trained with multi-sensory alignment followed by active-perception SFT. | Available |
| **ROMI-2K** | Real-world multi-sensory object interaction dataset covering nearly 2,000 objects and 6 atomic interactions with synchronized visual, audio, tactile, and force feedback. | Coming soon |
| **ROMA Bench** | 2,100 scene-level tasks (single-chain, multi-chain, and intent-driven) for evaluating active perception. | Coming soon |
| **Demo example scene** | One recorded tabletop scene (`example_data/1`) used by the local web demo. | Available |

## Checkpoint

The ROMA-7B checkpoint directory (`ROMA-Qwen2.5-Omni-7B`) contains:

```
ROMA-Qwen2.5-Omni-7B/
├── xxx.safetensors      # base Qwen2.5-Omni-7B model
├── anytouch2.pth        # tactile encoder
├── audio.bin            # fine-tuned audio adapter and encoder
├── tactile.bin          # fine-tuned tactile adapter
└── ROMA-LLM.bin         # ROMA LLM weights
```

The weights are loaded in this order: base Qwen2.5-Omni, tactile encoder, new action / modality tokens, audio adapter, tactile adapter, ROMA LLM. The loading code is in `demo.py` of the [GitHub repository](https://github.com/GeWu-Lab/ROMA).

## Dataset

**ROMI-2K** and **ROMA Bench** are **coming soon**. They will contain:

- **Handheld object collection:** 1,657 object-content combinations, each interacted with at 3 grasp locations using 6 atomic interactions, with wrist and third-person views, audio, and tactile feedback.
- **Tabletop scene collection (Training Set):** 400 scenes recorded with a robotic arm, with visual, audio, tactile, and force feedback, object bounding boxes, and annotations.
- **ROMA Bench:** 2,100 scene-level active-perception tasks built from the held-out test scenes.

## Usage

```bash
git clone https://github.com/GeWu-Lab/ROMA.git
cd ROMA
# see the GitHub README for environment setup

hf download GeWu-Lab/ROMA --repo-type dataset --local-dir resources
```

## Citation

```bibtex
@article{feng2026roma,
  title   = {ROMA: LLM System for Real-World Object-Centric Multi-Sensory Active Perception},
  author  = {Feng, Ruoxuan and Chen, Yutong and Song, Ruihua and Yang, Huan and
             Wang, Zhongyuan and Yao, Guocai and Hu, Di},
  journal = {arXiv preprint arXiv:2610.06955},
  url     = {https://arxiv.org/abs/2610.06955},
  year    = {2026}
}
```