Fast Plans, Faithful Actions: Closing the Planning-Execution Gap in Hierarchical Vision-Language-Action Models
cs.RO
Submitted: 2026-09-25
Updated: 2026-09-25
Code: https://github.com/Physical-Intelligence/openpi
Terminology
Sources
- PaliGemma: A versatile 3B VLM for transfer
- Classifier-Free Diffusion Guidance
- LoRA: Low-Rank Adaptation of Large Language Models
- NoTVLA: Semantics-Preserving Robot Adaptation via Narrative Action Interfaces
- 3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance
- LangForce: Bayesian Decomposition of Vision Language Action Models via Latent Action Queries
- Flow Matching for Generative Modeling
- GAE: Unleashing Physical Potential of VLM with Generalizable Action Expert
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- CEED-VLA: Consistency Vision-Language-Action Model with Early-Exit Decoding
- Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models
- Guided Flows for Generative Modeling and Decision Making
Related papers
- FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
- MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
- RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving