Riemannian Flow Matching Policy for Robot Motion Learning

arXiv:2403.10672v1 Announce Type: cross
Abstract: We introduce Riemannian Flow Matching Policies (RFMP), a novel model for learning and synthesizing robot visuomotor policies. RFMP leverages the efficient training and inference capabilities of flow matching methods. By design, RFMP inherits the strengths of flow matching: the ability to encode high-dimensional multimodal distributions, commonly encountered in robotic tasks, and a very simple and fast inference process. We demonstrate the applicability of RFMP to both state-based and vision-conditioned robot motion policies. Notably, as the …

abstract arxiv capabilities cs.lg cs.ro design encode flow inference multimodal novel policy robot training type