2025-06-25 カリフォルニア大学バークレー校（UC Berkeley）
Berkeley Humanoid Lite stands at about 1 meter and weighs approximately 16 kg. (Image courtesy of the researchers)
＜関連情報＞
- https://engineering.berkeley.edu/news/2025/06/berkeley-engineers-develop-customizable-3d-printed-robot-for-tech-newbies/
- https://roboticsconference.org/program/papers/62/
Berkeley Humanoid Liteのデモンストレーション： オープンソースでアクセス可能でカスタマイズ可能な3Dプリントヒューマノイドロボット Demonstrating Berkeley Humanoid Lite: An Open-source, Accessible, and Customizable 3D-printed Humanoid Robot
Yufeng Chi, Qiayuan Liao, Junfeng Long, Xiaoyu Huang, Sophia Shao, Borivoje Nikolic, Zhongyu Li, Koushil Sreenath
2025 Robotics Science and Systems conference Poster Session (Day 2): Sunday, June 22, 6:30-8:00 PM
Abstract
Despite significant interest and advancements in humanoid robotics, most existing commercially available hardware remains high-cost, closed-source, and non-transparent within the robotics community. This lack of accessibility and customization hinders the growth of the field and the broader development of humanoid technologies. To address these challenges and promote democratization in humanoid robotics, we demonstrate Berkeley Humanoid Lite, an open-source humanoid robot designed to be accessible, customizable, and beneficial for the entire community. The core of this design is a modular 3D-printed gearbox for the actuators and robot body. All components can be sourced from widely available e-commerce platforms and fabricated using standard desktop 3D printers, keeping the total hardware cost under $6,000 (based on U.S. market prices). The design emphasizes modularity and ease of fabrication. To address the inherent limitations of 3D-printed gearboxes, such as reduced strength and durability compared to metal alternatives, we adopted a cycloidal gear design, which provides an optimal form factor in this context. Extensive testing was conducted on the 3D-printed actuators to validate their durability and alleviate concerns about the reliability of plastic components. To demonstrate the capabilities of Berkeley Humanoid Lite, we conducted a series of experiments, including the development of a locomotion controller using reinforcement learning. These experiments successfully showcased zero-shot policy transfer from simulation to hardware, highlighting the platform’s suitability for research validation. By making the hardware design, embedded code, and training and deployment frameworks fully open-source and globally accessible, we aim for Berkeley Humanoid Lite to serve as a pivotal step toward democratizing the development of humanoid robotics.
