# AgiBot-World
**Repository Path**: sungq5/AgiBot-World
## Basic Information
- **Project Name**: AgiBot-World
- **Description**: 稚晖君
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-01-03
- **Last Updated**: 2025-01-03
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README

[](https://huggingface.co/agibot-world) [](https://agibot-world.com) 
## Key Features 🔑
- **1 million+** trajectories from 100 robots.
- **100+ 1:1 replicated real-life scenarios** across 5 target domains.
- **Cutting-edge hardware:** visual tactile sensors / 6-DoF Dexterous hand / mobile dual-arm robots
- **Wide-spectrum versatile challenging tasks**
Contact-rich Manipulation
|
Long-horizon Planning
|
Multi-robot Collaboration
|
## News📰
- **`[2024/12/30]`** 🤖 Agibot World Alpha released.
## Table of Contents
1. [Key Features](#keyfeatures)
2. [Getting Started](#gettingstarted)
- [How to Get Started with Our AgiBot World Data](#preaparedata)
- [Policy Learning Quickstart](#training)
3. [TODO List](#todolist)
4. [License and Citation](#liscenseandcitation)
## Getting started 🔥
#### How to Get Started with Our AgiBot World Data
Download data from our [HuggingFace](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Alpha) page.
``` your settings: https://huggingface.co/settings/tokens
git clone https://huggingface.co/datasets/agibot-world/AgiBotWorld-Alpha
```
Convert the data to **LeRobot Dataset** format following the detailed instructions [here](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Alpha#dataset-preprocessing).
#### Policy Training Quickstart
Leveraging the simplicity of [LeRobot Dataset](https://github.com/huggingface/lerobot), we provide a user-friendly [Jupyter Notebook](https://github.com/OpenDriveLab/AgiBot-World/blob/main/AgibotWorld.ipynb) for training diffusion policy on AgiBot World Dataset.
## TODO List 📅
- [x] **AgiBot World Alpha**
- [ ] **AgiBot World Beta** (expected Q1 2025)
- [ ] ~1,000,000 trajectories of high-quality robot data
- [ ] ACT、DP3、OpenVLA and some other baseline models
- [ ] **AgiBot World Colosseum** (expected 2025)
- [ ] A comprehensive platform with toolkits including teleoperation, training and inference.
- [ ] **2025 AgiBot World Challenge** (expected 2025)
## License and Citation📄
All the data and code within this repo are under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). Please consider citing our project if it helps your research.
```BibTeX
@misc{contributors2024agibotworldrepo,
title={AgiBot World Colosseum},
author={AgiBot World Colosseum contributors},
howpublished={\url{https://github.com/OpenDriveLab/AgiBot-World}},
year={2024}
}
```