Same-category comparison
Name	Rank	Metrics
opendatalab/OmniDocBench	5,174	Language: Python Stars: 2,111 Forks: 204 Description: [CVPR 2025] A Comprehensive Benchmark for Document Parsing and Evaluation.
bgshih/crnn	5,176	Language: Lua Stars: 2,103 Forks: 546 Description: Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
candlewill/Dialog_Corpus	5,188	Language: Python Stars: 2,057 Forks: 485
2U1/Qwen-VL-Series-Finetune	5,224	Language: Python Stars: 1,981 Forks: 224 Description: An open-source implementaion for fine-tuning Qwen-VL series by Alibaba Cloud.
adobe-research/custom-diffusion	5,228	Language: Python Stars: 1,977 Forks: 139 Description: Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023).
Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor	5,229	Language: JavaScript Stars: 1,976 Forks: 446 Description: Web labeling tool for bitmap images and point clouds.
mit-han-lab/once-for-all	5,235	Language: Python Stars: 1,955 Forks: 345 Description: [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment.
AI4Finance-Foundation/FinRL-Meta	5,238	Language: Python Stars: 1,950 Forks: 749 Description: FinRL®-Meta: Dynamic datasets and market environments for FinRL.

Name

Rank

Metrics

5,174

Language:: Python
Stars:: 2,111
Forks:: 204
Description:: [CVPR 2025] A Comprehensive Benchmark for Document Parsing and Evaluation.

bgshih/crnn

5,176

Language:: Lua
Stars:: 2,103
Forks:: 546
Description:: Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

candlewill/Dialog_Corpus

5,188

Language:: Python
Stars:: 2,057
Forks:: 485

2U1/Qwen-VL-Series-Finetune

5,224

Language:: Python
Stars:: 1,981
Forks:: 224
Description:: An open-source implementaion for fine-tuning Qwen-VL series by Alibaba Cloud.

adobe-research/custom-diffusion

5,228

Language:: Python
Stars:: 1,977
Forks:: 139
Description:: Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023).

Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor

5,229

Language:: JavaScript
Stars:: 1,976
Forks:: 446
Description:: Web labeling tool for bitmap images and point clouds.

mit-han-lab/once-for-all

5,235

Language:: Python
Stars:: 1,955
Forks:: 345
Description:: [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment.

AI4Finance-Foundation/FinRL-Meta

5,238

Language:: Python
Stars:: 1,950
Forks:: 749
Description:: FinRL®-Meta: Dynamic datasets and market environments for FinRL.

Key parameters and specifications
Parameter	Value
Language	Python
Category	Model Development
Subcategory	Environments, Physical AI
Keywords	3D, Data processing, Embodied, Robotics
Stars	1,980
Forks	317
Contributors	4
Created date	2025-03-17
Updated date	2026-10-16
Stars in 1 day	1
Stars in 7 days	8
Rank	5,225
Previous rank	9,196
Rank change	3,971
7-day stars rank	4,445
Previous 7-day stars rank	19,032
7-day stars rank change	14,587
Total stars rank	6,404
Previous total stars rank	6,401
Total stars rank change	-3

Parameter

Value

Language

Python

Berkeley Humanoid Lite

Berkeley Humanoid Lite is an open-source, sub-$5,000 humanoid robot featuring modular 3D-printed gearboxes and widely available components, designed to democratize and advance humanoid robotics research.

This project is built on the values of open-source, accessibility, and customization, and it's continuously evolving. We welcome your feedback, issues, and pull requests on GitHub or joining our Discord.

Overview

This repository is the workspace for the Berkeley Humanoid Lite project that contains everything we need, including policy training, sim2sim validation, real-world deployment, motion capture, and teleoperated manipulation controls.

Functionalities are organized into several submodules. We arrange the directory structure following the Isaac Lab convention, where each submodule can be installed as an extension:

source/berkeley_humanoid_lite/ contains the IsaacLab environment and task definitions.
source/berkeley_humanoid_lite_assets/ contains robot descriptions (URDF, MJCF, and USD) and the script to export these description files from Onshape project.
source/berkeley_humanoid_lite_lowlevel/ contains the lowlevel code running on the real robot. Only contents inside this folder are required to deploy to the real robot.

Except a few edge cases, all the commands should be invoked from the root directory of this repository. The entry points of different flows are collected in the scripts/ directory.

Getting Started

Please refer to our Documentation to get started with software and hardware setup.

The latest release of CAD model and 3D print files can be accessed from the Release page.

Contributing

We wholeheartedly welcome contributions from the community to make this robot platform more mature and useful for everyone. We appreciate any kind of contributions, including bug reports, feature requests, or code contributions.

Also, please reach out to us to tell us about your projects and how you are using this robot platform. We would love to feature your work on our website and social media.

License

The code in this repository is licensed under MIT License. See the LICENSE file for details.

Other assets are under Creative Commons Attribution-ShareAlike 4.0 International .

Citation

If you find this code useful, we would appreciate it if you would cite our paper:

@article{chi2025demonstrating,
  title={Demonstrating Berkeley Humanoid Lite: An Open-source, Accessible, and Customizable 3D-printed Humanoid Robot},
  author={Yufeng Chi and Qiayuan Liao and Junfeng Long and Xiaoyu Huang and Sophia Shao and Borivoje Nikolic and Zhongyu Li and Koushil Sreenath},
  year={2025},
  eprint={2504.17249},
  archivePrefix={arXiv},
  primaryClass={cs.RO},
  url={https://arxiv.org/abs/2504.17249}, 
}

berkeley-humanoid-lite

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