FAFM performs flow matching in the frequency domain using DCT on action sequences to produce continuous temporally consistent robotic actions with a Sobolev-style smoothness regularizer.
Frmd: Fast robot motion diffusion with consistency-distilled movement primitives for smooth action generation.arXiv preprint arXiv:2503.02048, 2025
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SCP integrates diffusion-based imitation learning with Gaussian-encoded surface constraints and dynamic movement primitives to generate actions with improved success rates and contact stability on free-form surfaces.
citing papers explorer
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Frequency-Aware Flow Matching for Continuous and Consistent Robotic Action Generation
FAFM performs flow matching in the frequency domain using DCT on action sequences to produce continuous temporally consistent robotic actions with a Sobolev-style smoothness regularizer.
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Surface Constraint Policy for Learning Surface-Constrained and Dynamically Feasible Robot Skills
SCP integrates diffusion-based imitation learning with Gaussian-encoded surface constraints and dynamic movement primitives to generate actions with improved success rates and contact stability on free-form surfaces.