Barrier-Constrained Guidance For Real-time Asynchronous VLA Execution
cs.RO
Submitted: 2026-10-10
Updated: 2026-10-10
Code: https://github.com/Stanford-ILIAD/openvla-mini
Sources
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- OpenVLA: An Open-Source Vision-Language-Action Model
- SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
- LaST$_{0}$: Latent Spatio-Temporal Chain-of-Thought for Robotic Vision-Language-Action Model
- Reinforcement Learning with Action Chunking
- Running VLAs at Real-time Speed
- Leave No Observation Behind: Real-time Correction for VLA Action Chunks
- Asynchronous Fast-Slow Vision-Language-Action Policies for Whole-Body Robotic Manipulation
- VLASH: Real-Time VLAs via Future-State-Aware Asynchronous Inference
- DynamicVLA: A Vision-Language-Action Model for Dynamic Object Manipulation
- Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution
- Gemini Robotics: Bringing AI into the Physical World
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion Models
- Imitating Human Behaviour with Diffusion Models
- Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
- DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching
- Streaming Flow Policy: Simplifying diffusion/flow-matching policies by treating action trajectories as flow trajectories
- DEFLECT: Temporal Counterfactual Preference Learning for Delay-Robust Asynchronous VLAs
- StreamingVLA: Streaming Vision-Language-Action Model with Action Flow Matching and Adaptive Early Observation
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- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies