发表机构
AMD AIG Team; Beijing Institute of Technology（AMD人工智能团队; 北京理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对视觉-语言-动作操纵提出基于AMD ROCm的Real2Sim2Real技术栈，涵盖多硬件计算，由开放软件栈统一。通过四个演示表明无需CUDA锁定生态系统，展示了在多硬件平台上的相关成果，且管道可在特定硬件和平台上原生运行并重现。
AI 中文摘要
物理人工智能，即将大型视觉-语言-动作（VLA）模型与在现实世界中行动的具身智能体相结合，已成为人工智能的下一个主要前沿领域。本文提出了一个用于具身操纵的端到端、完全由AMD加速的技术栈，涵盖数据中心训练芯片、Radeon PRO模拟/渲染GPU和Ryzen AI边缘计算，由开放的ROCm软件栈统一。通过四个渐进式演示表明，训练和部署基于VLA的操纵策略不需要CUDA锁定的生态系统。演示包括用SmolVLA训练并部署在物理Franka手臂上的模拟到现实操纵管道、语义语言基础的对象选择任务、融合真实场景3D高斯溅射重建与Genesis物理引擎的Real2Sim合成数据生成管道，以及在多个硬件平台上进行的四足和人形机器人运动的大规模强化学习。所有管道都能在RDNA4和RDNA3.5硬件上的ROCm + PyTorch上原生运行，且可在免费的Radeon云平台上重现。
英文摘要
Physical AI -- the integration of large vision-language-action (VLA) models with embodied agents that act in the real world -- has emerged as the next major frontier for AI, echoed by industry leaders such as Jensen Huang (``the next big thing is Physical AI, AI with a body,'' GTC Paris, June 2025) and Dr. Lisa Su (`we're entering the world of Physical AI ... this is where AI enters the real world,' CES 2026). This paper presents an end-to-end, fully AMD-accelerated technology stack for embodied manipulation, spanning data-center training silicon, Radeon PRO simulation/rendering GPUs, and Ryzen AI edge compute, unified by the open ROCm software stack. We demonstrate that training and deploying VLA-based manipulation policies does not require a CUDA-locked ecosystem. Four progressive demonstrations are presented: (1) a Sim-to-Real manipulation pipeline trained with SmolVLA and deployed on a physical Franka arm; (2) a semantic, language-grounded object-selection task (`one-of-three'); (3) a Real2Sim synthetic-data generation pipeline that fuses 3D Gaussian Splatting (3DGS) reconstructions of real scenes with the Genesis physics engine; and (4) large-scale reinforcement learning for quadruped and humanoid locomotion benchmarked across multiple hardware platforms. All pipelines run natively on ROCm + PyTorch on RDNA4 (Radeon AI PRO R9700) and RDNA3.5 (Radeon PRO W7900) hardware and are reproducible on the free Radeon Cloud Platform.
