Overcoming Robot Diffusion Policy Latency: Achieving Sub-Millisecond Inference

chris_j_paxton · x · 2026-08-05

Diffusion Policy has been a major breakthrough for real-world robot learning, but its reliance on computing action trajectories from random noise introduces high latency.

Researchers propose initializing the search based on previous actions. This enables incredibly fast policy inference with sub-millisecond latency and often improves generalization, generating high-quality predictions.

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Overcoming Robot Diffusion Policy Latency: Achieving Sub-Millisecond Inference

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