Jim Fan· @DrJimFan · X·· 2025-03-21精选
AI 导读
NVIDIA 发布世界首个开源人形机器人基础模型 GR00T N1,仅 2B 参数,采用 VLM 加 Diffusion Transformer 架构实现端到端控制。模型基于真实遥操作、30 万+仿真轨迹及合成神经轨迹训练,在 GR1、1X Neo 等机器人上任务性能提升 30%,并可跨具身部署至百元级开源机械臂。
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NVIDIA开源首个通用人形机器人基础模型GR00T N1,2B参数可部署于百元级机械臂
正文 · 原文
We got lots of great community feedback on our open-source GR00T N1! Check out our Github, star, fork, contribute back! Let's solve generally intelligent robots together, one commit at a time.
https://github.com/NVIDIA/Isaac-GR00T/ https://t.co/ghmXrwuMPC
Excited to announce GR00T N1, the world’s first open foundation model for humanoid robots! We are on a mission to democratize Physical AI. The power of general robot brain, in the palm of your hand - with only 2B parameters, N1 learns from the most diverse physical action dataset ever compiled and punches above its weight: - Real humanoid teleoperation data. - Large-scale simulation data: we are open-sourcing 300K+ trajectories! - Neural trajectories: we apply SOTA video generation models to “hallucinate” new synthetic data that features accurate physics in pixels. Using Jensen’s words, “systematically infinite data”! - Latent actions: we develop novel algorithms to extract action tokens from in-the-wild human videos and neural generated videos. GR00T N1 is a single end-to-end neural net, from photons to actions: - Vision-Language Model (System 2) that interprets the physical world through vision and language instructions, enabling robots to reason about their environment and instructions, and plan the right actions. - Diffusion Transformer (System 1) that “renders” smooth and precise motor actions at 120 Hz, executing the latent plan made by System 2. We deploy N1 on GR1 robot, 1X Neo robot, and a large collection of simulation benchmarks. N1 achieves up to +30% boost in diverse manipulation tasks for household and industrial settings. While humanoid robots are the main focus of N1, our model also supports cross-embodiment. We finetune it to work on the $110 HuggingFace LeRobot SO100 robot arm! Open robot brain runs on open hardware. Sounds just right. Let’s solve robotics, together, one token at a time. Links to our Whitepaper, Github repo, HuggingFace model, and open dataset page in the thread: 🧵在 X 查看被引用的帖子
来源:Jim Fan · x.com