开源低成本3D打印人形机器人,助力机器人研究民主化
Demonstrating Berkeley Humanoid Lite: An Open-source, Accessible, and Customizable 3D-printed Humanoid Robot

- 模块化3D打印齿轮箱设计,可家用打印机制造
- 总硬件成本低于5000美元,支持零样本仿真到硬件迁移
- 适合科研、教育及开源社区使用,代码与设计全公开
尽管人形机器人领域备受关注并取得进展,但多数商业化硬件仍价格高昂、闭源且不透明,限制了领域发展与技术普及。为应对这一挑战,我们推出了伯克利人形机器人轻量版(Berkeley Humanoid Lite),一款开源、低成本、可定制的3D打印人形机器人。其核心为模块化3D打印电机减速箱,所有组件均可通过主流电商采购,并用普通桌面3D打印机制造,整体硬件成本低于5000美元(基于美国市场价格)。为克服塑料齿轮箱强度不足的问题,采用环形齿轮结构以优化性能。通过大量测试验证了3D打印执行器的耐用性。实验中,利用强化学习开发行走控制器,成功实现从仿真到硬件的零样本策略迁移,证明平台具备研究验证价值。所有硬件设计、嵌入式代码及训练部署框架均开源,网址为 https://lite.berkeley-humanoid.org。
原文摘要 · Abstract (English)
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 $5,000 (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 fully open-sourcing the hardware design, embedded code, and training and deployment frameworks, we aim for Berkeley Humanoid Lite to serve as a pivotal step toward democratizing the development of humanoid robotics. All resources are available at https://lite.berkeley-humanoid.org.
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