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agibot_world

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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

Contact-rich Manipulation

 Long-horizon Planning

Long-horizon Planning

 Multi-robot Collaboration

Multi-robot Collaboration

News📰

  • [2025/01/03] Agibot World Alpha Sample Dataset released.
  • [2024/12/30] 🤖 Agibot World Alpha released.

Table of Contents

  1. Key Features
  2. At a Quick Glance
  3. Getting Started
  4. TODO List
  5. License and Citation

At a Quick Glance⬇️

Follow the steps below to quickly explore and get an overview of AgiBot World with our sample dataset (~7GB).

# Installation
conda create -n agibotworld python=3.10 -y
conda activate agibotworld
git clone https://github.com/huggingface/lerobot.git
cd lerobot
pip install -e .
pip install matplotlib
cd ..
git clone https://github.com/OpenDriveLab/AgiBot-World.git
cd AgiBot-World

# Download the sample dataset (~7GB) from Hugging Face. Replace <your_access_token> with your Hugging Face Access Token. You can generate an access token by following the instructions in the Hugging Face documentation from https://huggingface.co/docs/hub/security-tokens
mkdir data
cd data
curl -L -o sample_dataset.tar -H "Authorization: Bearer <your_access_token>" https://huggingface.co/datasets/agibot-world/AgiBotWorld-Alpha/resolve/main/sample_dataset.tar
tar -xvf sample_dataset.tar

# Convert the sample dataset to LeRobot dataset format and visualize
cd ..
python scripts/convert_to_lerobot.py --src_path ./data/sample_dataset --task_id 390 --tgt_path ./data/sample_lerobot
python scripts/visualize_dataset.py --task-id 390 --dataset-path ./data/sample_lerobot

Getting started 🔥

Installation

Download our source code:

git clone https://github.com/OpenDriveLab/AgiBot-World.git
cd AgiBot-World

Our project is built upon the lerobot library (dataset v2.0), please follow their installation instructions.

How to Get Started with Our AgiBot World Data 

pip install openxlab # install CLI
openxlab dataset get --dataset-repo OpenDriveLab/AgiBot-World # dataset download
huggingface-cli download --resume-download --repo-type dataset agibot-world/AgiBotWorld-Alpha --local-dir ./AgiBotWorld-Alpha

Convert the data to LeRobot Dataset format.

python scripts/convert_to_lerobot.py --src_path /path/to/agibotworld/alpha --task_id 390 --tgt_path /path/to/save/lerobot

Visualize Datasets

We adapt and extend the dataset visualization script from LeRobot Project

python scripts/visualize_dataset.py --task-id 390 --dataset-path /path/to/lerobot/format/dataset

It will open rerun.io and display the camera streams, robot states and actions, like this:

Policy Training Quickstart

Leveraging the simplicity of LeRobot Dataset, we provide a user-friendly Jupyter Notebook for training diffusion policy on AgiBot World Dataset.

TODO List 📅

  • 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. Please consider citing our project if it helps your research.

@misc{contributors2024agibotworldrepo,
  title={AgiBot World Colosseum},
  author={AgiBot World Colosseum contributors},
  howpublished={\url{https://github.com/OpenDriveLab/AgiBot-World}},
  year={2024}
}