Xuning Yang

When every generalist robot model scores 95%+ on a benchmark, the numbers become meaningless. What if we built a photorealistic benchmark that never saturates and can generate new scenes and tasks with AI Workflows in minutes? We introduce RoboLab! 🧵(1/6)

@wang_siyin Results coming soon, will be updated on the website

@xuningy how about the performance of recent WAMs like Dreamzero

When every generalist robot model scores 95%+ on a benchmark, the numbers become meaningless. What if we built a photorealistic benchmark that never saturates and can generate new scenes and tasks with AI Workflows in minutes? We introduce RoboLab! 🧵(1/6)

a new form of greeting has dropped: see you at icml🇰🇷 1/1 accepted to ICML. more details soon

We are still far from zero-shot policy deployment on new tasks

@YuXiang_IRVL Far from it, but the field is moving fast. We have results from DreamZero coming very soon.

Generalist robot policies need a benchmark that works across any robot and any policy. 🦾 Introducing RoboLab, a high‑fidelity simulation benchmark built on NVIDIA Isaac and Omniverse to evaluate generalist robot policies in diverse, photoreal, physics‑based environments. Coming soon to the NVIDIA Isaac Lab‑Arena roadmap for large‑scale, robotic policy evaluation. 📖 nvda.ws/47RbOgX #NationalRoboticsWeek

RoboLab comes with RoboLab-120 — a curated, diverse benchmark of 120 tasks to get started. Set up and run in <20 min. (6/6) Try it out 👇 🌐 research.nvidia.com/labs/srl/proje… 📄 arxiv.org/abs/2604.09860 💻 github.com/NVLabs/RoboLab

→ Customization: Comes with 200+ objects, 100+ backgrounds, lighting, camera poses… don’t like it? No problem, add your own → Diagnostics: motion quality, failure events, + sensitivity analysis for failure attribution (5/6)