OpenEAI-Platform: An Open-source Embodied Artificial Intelligence Hardware-Software Unified Platform
2026-06-02 • Robotics
Robotics
AI summaryⓘ
The authors created an open-source robot arm and a vision-language-action model that work together to perform tasks. Their robot arm design is low-cost but accurate, and their AI model learns from publicly available data. In real-world tests, their arm did better than some commercial robot arms using the same AI, and their AI performed about as well as a popular large pretrained model even with less training data. They plan to share all their designs, code, and models so others can build on their work.
Embodied AIRobotic armVision-language-action (VLA)Degrees of freedom (dof)Open-source hardwareDiffusion TransformerMultimodal datasetsPretrainingReproducible research
Authors
Jinyuan Zhang, Luoyi Fan, Leiyu Wang, Yeqiang Wang, Yicheng Zhu, Cewu Lu, Nanyang Ye
Abstract
Embodied AI in the real world requires both accurate hardware and robust vision-language-action (VLA) policies. We present OpenEAI-Platform, a fully open-source platform that integrates a low-cost 6+1 degree-of-freedom (dof) robotic arm (OpenEAI-Arm) and a reproducible VLA model (OpenEAI-VLA). OpenEAI-Arm provides open-source mechanical designs for low manufacturing cost and compliant control methods for higher accuracy. OpenEAI-VLA builds on Qwen3-VL-4B and uses a Diffusion Transformer action head, and is trained in two stages with only open-source robot and multimodal datasets. Across four real-world manipulation tasks, OpenEAI-Arm outperforms two commercial 6+1-dof arms under the same policy, and OpenEAI-VLA achieves success rates comparable to the large-scale pretrained pi0 baseline with only limited pretraining data. We will release the full hardware designs, drivers, models, and training/data pipelines to support reproducible research and scalable data collection. Our codes, layouts, and models will be released after the paper is accepted.