Uranus: Building the Next-Generation Simulation Infrastructure for Embodied AI
Scalable simulation is essential for robot data generation, policy training, evaluation, and safe iteration, yet real-world interaction is costly and conventional simulators require labor-intensive construction. We present Uranus, a data-driven robot simulator built around a joint-trajectory-conditioned autoregressive diffusion model. Uranus offers three key capabilities: (1) streaming, open-ended rollout, which receives future joint-position trajectories online and autoregressively generates one latent frame per step, corresponding to four RGB frames, without a fixed horizon; (2) low-latency generation, achieving 24 FPS after inference optimization; and (3) scalable, extensible robot con...
| Authors | Wenkang Qin, Yukun Zhou, Noah Shen et al. |
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| Primary category | cs.RO |
| Published | 21 September 2026 |
| Last updated at source | 23 September 2026 |
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