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https://github.com/deepmodeling/Uni-Lab-OS
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- MagazineHolder: klasses=None，解耦极片子节点初始化 - Magazine: 重写 serialize/deserialize，截断旧极片脏数据 - bottle_carriers: 移除 YIHUA_Electrolyte_12VialCarrier 初始化填瓶 - decks.py: BIOYOND_YB_Deck→BioyondElectrolyteDeck，移除 setup 参数 - YB_YH_materials.py: CoincellDeck→YihuaCoinCellDeck，新增 electrolyte_buffer 槽位 - resource_tracker.py: Container 状态键预填 + 重复 UUID 自动修复 + 树级名称去重 - itemized_carrier.py: XY 近似坐标匹配，修复 Z 偏移问题 - bioyond_cell_workstation.py: 跨站转运改用真实资源 + 类型映射双模式查找 - station.py: sync_to_external 属性访问路径修复 - coin_cell_assembly.py: 新增 10 个 Modbus 余量属性 - CSV/JSON/YAML 配置同步更新（类名重命名 + 移除 setup） - 新增 changelog_2026-03-12.md
Uni-Lab-OS
English | 中文
Uni-Lab-OS is a platform for laboratory automation, designed to connect and control various experimental equipment, enabling automation and standardization of experimental workflows.
Key Features
- Multi-device integration management
- Automated experimental workflows
- Cloud connectivity capabilities
- Flexible configuration system
- Support for multiple experimental protocols
Documentation
Detailed documentation can be found at:
Quick Start
1. Setup Conda Environment
Uni-Lab-OS recommends using mamba for environment management. Choose the package that fits your needs:
| Package | Use Case | Contents |
|---|---|---|
unilabos |
Recommended for most users | Complete package, ready to use |
unilabos-env |
Developers (editable install) | Environment only, install unilabos via pip |
unilabos-full |
Simulation/Visualization | unilabos + ROS2 Desktop + Gazebo + MoveIt |
# Create new environment
mamba create -n unilab python=3.11.14
mamba activate unilab
# Option A: Standard installation (recommended for most users)
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
# Option B: For developers (editable mode development)
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# Then install unilabos and dependencies:
git clone https://github.com/deepmodeling/Uni-Lab-OS.git && cd Uni-Lab-OS
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
# Option C: Full installation (simulation/visualization)
mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
When to use which?
- unilabos: Standard installation for production deployment and general usage (recommended)
- unilabos-env: For developers who need
pip install -e .editable mode, modify source code - unilabos-full: For simulation (Gazebo), visualization (rviz2), and Jupyter notebooks
2. Clone Repository (Optional, for developers)
# Clone the repository (only needed for development or examples)
git clone https://github.com/deepmodeling/Uni-Lab-OS.git
cd Uni-Lab-OS
- Start Uni-Lab System
Please refer to Documentation - Boot Examples
- Best Practice
Message Format
Uni-Lab-OS uses pre-built unilabos_msgs for system communication. You can find the built versions on the GitHub Releases page.
Citation
If you use Uni-Lab-OS in academic research, please cite:
@article{gao2025unilabos,
title = {UniLabOS: An AI-Native Operating System for Autonomous Laboratories},
doi = {10.48550/arXiv.2512.21766},
publisher = {arXiv},
author = {Gao, Jing and Chang, Junhan and Que, Haohui and Xiong, Yanfei and
Zhang, Shixiang and Qi, Xianwei and Liu, Zhen and Wang, Jun-Jie and
Ding, Qianjun and Li, Xinyu and Pan, Ziwei and Xie, Qiming and
Yan, Zhuang and Yan, Junchi and Zhang, Linfeng},
year = {2025}
}
License
This project uses a dual licensing structure:
- Main Framework: GPL-3.0 - see LICENSE
- Device Drivers (
unilabos/devices/): DP Technology Proprietary License
See NOTICE for complete licensing details.
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Contact Us
- GitHub Issues: https://github.com/deepmodeling/Uni-Lab-OS/issues