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---
title: "DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution"
emoji: 🤖
colorFrom: blue
colorTo: green
sdk: gradio
app_file: app.py
pinned: false
license: llama3.1
---
<div align="center">
<h1>DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models (Spaces)</h1>
<div class="project-info">
This project is part of the <a href="https://moonshot-cafe-project.org/en/" target="_blank">Moonshot Café Project</a>
</div>
<div class="authors">
<a href="https://researchmap.jp/wangyongdong?lang=en" target="_blank">Yongdong Wang</a><sup class="org-1">1,*</sup>,
Runze Xiao<sup class="org-1">1</sup>,
<a href="https://www.robot.t.u-tokyo.ac.jp/~louhi_kasahara/index-e.html" target="_blank">Jun Younes Louhi Kasahara</a><sup class="org-1">1</sup>,
<a href="https://researchmap.jp/r-yaj?lang=en" target="_blank">Ryosuke Yajima</a><sup class="org-1">1</sup>,
<a href="http://k-nagatani.org/" target="_blank">Keiji Nagatani</a><sup class="org-1">1</sup><sup class="org-2">, 2</sup>,
<a href="https://www.robot.t.u-tokyo.ac.jp/~yamashita/" target="_blank">Atsushi Yamashita</a><sup class="org-3">3</sup>,
<a href="https://www.robot.t.u-tokyo.ac.jp/asamalab/en/members/asama/biography.html" target="_blank">Hajime Asama</a><sup class="org-4">4</sup>
</div>
<div class="affiliations">
<sup class="org-1">1</sup>Graduate School of Engineering, The University of Tokyo<br>
<sup class="org-2">2</sup>Faculty of Systems and Information Engineering, University of Tsukuba<br>
<sup class="org-3">3</sup>Graduate School of Frontier Sciences, The University of Tokyo<br>
<sup class="org-4">4</sup>Tokyo College, The University of Tokyo
</div>
<div class="corresponding-author">
*Corresponding author: <a href="mailto:[email protected]">[email protected]</a>
</div>
<div align="center">
<a href="https://arxiv.org/pdf/2411.09022" target="_blank" rel="noopener noreferrer">
<img src="https://img.shields.io/badge/arXiv-2411.09022-b31b1b" alt="arXiv Badge">
</a>
<a href="https://github.com/wyd0817/QA_LLM_Module" target="_blank" rel="noopener noreferrer">
<img src="https://img.shields.io/badge/QA_LLM_Module-GitHub-blue" alt="QA LLM Module GitHub Badge">
</a>
<a href="https://huggingface.co/datasets/YongdongWang/dart_llm_tasks" target="_blank" rel="noopener noreferrer">
<img src="https://img.shields.io/badge/Dataset-Hugging_Face-blue" alt="Dataset Badge">
</a>
<a href="https://huggingface.co/spaces/YongdongWang/DART-LLM-Llama3.1-8b" target="_blank" rel="noopener noreferrer">
<img src="https://img.shields.io/badge/Spaces-DART--LLM--Llama3.1--8b-lightgrey" alt="Spaces Badge">
</a>
<a href="https://www.youtube.com/watch?v=p3A-yg3yv0Q" target="_blank" rel="noopener noreferrer">
<img src="https://img.shields.io/badge/Video-YouTube-red" alt="Video Badge">
</a>
<a href="https://www.youtube.com/watch?v=T3M94hP8NFQ" target="_blank" rel="noopener noreferrer">
<img src="https://img.shields.io/badge/Real_Robot-YouTube-orange" alt="Real Robot Badge">
</a>
</div>
## Overview
This Hugging Face Space hosts DART-LLM, a QLoRA-fine-tuned meta-llama/Llama-3.1-8B model specialized in construction robotics. It demonstrates converting natural language robot commands into structured JSON tasks, supporting detailed multi-robot coordination, spatial reasoning, and action planning.
## Quick Start
1. Enter your robot command in the provided interface.
2. Click **Generate Tasks**.
3. Review the structured JSON output describing the robot task sequence.
## Citation
If you use this work, please cite:
```bibtex
@article{wang2024dart,
title={Dart-llm: Dependency-aware multi-robot task decomposition and execution using large language models},
author={Wang, Yongdong and Xiao, Runze and Kasahara, Jun Younes Louhi and Yajima, Ryosuke and Nagatani, Keiji and Yamashita, Atsushi and Asama, Hajime},
journal={arXiv preprint arXiv:2411.09022},
year={2024}
}
``` |