SOURCE-LINKED INTELLIGENCE
Faster Visuomotor Policy Learning on Action Manifolds via Riemannian MeanFlow
Visuomotor policies learn a direct map from raw sensory observations to robot action sequences. Policies based on Diffusion and Flow Matching capture the multimodal distribution over action sequences in an end-to-end manner. This expressivity comes at the cost of multi-step numerical integration of the learned vector field for action generation, which can be expensive and time-consuming, impeding fast control rates required in robotics applications. Furthermore, robot action sequences are usually defined on a smooth, differentiable manifold, requiring that the learned policy respects the intri
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T17:00:57.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.