Reactive Real-Time Flow Policies via Asynchronous Distribution Alignment

arXiv:2609.36540 · cs.RO, cs.LG · Submitted 2026-09-29 · Read on arXiv

cs.RO, cs.LG

Submitted: 2026-09-29

Updated: 2026-09-29

Project page: https://tminka.github.io/papers/ep

Terminology

• Distillation — 19× in this paper · explained in 2 episodes
• Recursive Flow-Field Distillation — 11× in this paper
• Alignment — 6× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Action Chunking — 5× in this paper · explained in 1 episode
• Generalization — 4× in this paper · explained in 13 episodes
• Real-Time Chunking — 4× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Distribution Matching — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Flow Matching — 2× in this paper · explained in 7 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency Distillation — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Self-distillation — 1× in this paper · explained in 6 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes

Sources

• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• Training-Time Action Conditioning for Efficient Real-Time Chunking
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• RT-1: Robotics Transformer for Real-World Control at Scale
• DREAM-Chunk: Reactive Action Chunking with Latent World Model
• Open X-Embodiment: Robotic Learning Datasets and RT-X Models
• Start Right, Arrive Right: Asynchronous Execution via Initial Noise Selection
• FutureRTC: Real-Time Robot Execution with Anticipatory-Conditioned Action Chunking
• OpenVLA: An Open-Source Vision-Language-Action Model
• Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
• Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control?
• CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation
• FASTER: Rethinking Real-Time Flow VLAs
• SnapFlow: One-Step Action Generation for Flow-Matching VLAs via Progressive Self-Distillation
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• Octo: An Open-Source Generalist Robot Policy
• $\pi\mathbf{R}^2$: Reactive Real-time Flow Policies
• $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
• Consistency Policy: Accelerated Visuomotor Policies via Consistency Distillation

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