D-Robotics open-sources a diffusion-based robot simulator; its 24-frames-per-second claim is self-reported
Uranus uses autoregressive diffusion for robot simulation with code and weights released, but all metrics are author-reported and the paper was withdrawn once, so treat it as a signal to track.
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D-Robotics AI Lab has released Uranus, an open-source robot simulator built on a joint-trajectory-conditioned autoregressive diffusion model, with code, SDK and model weights published together.
The paper claims three capabilities: streaming rollout that consumes future joint trajectories frame by frame with no fixed horizon; 24 FPS after inference optimization; and a unified interface across robot embodiments and multi-view camera setups. All of these numbers are first-party, self-reported results with no independent reproduction yet.
One detail worth noting: version 2 of the paper was withdrawn and resubmitted as v3. The authors say the paper includes out-of-distribution evaluation and states current limitations. Teams doing robot data generation or policy evaluation can pull the weights and test the claims directly.