Sequential Planning via Anchored Robotic Keypoints
cs.RO
Submitted: 2026-06-29
Updated: 2026-10-12
Terminology
Sources
- OpenVLA: An Open-Source Vision-Language-Action Model
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- MolmoAct2: Action Reasoning Models for Real-world Deployment
- LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
- LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
- Not All Features Are Created Equal: A Mechanistic Study of Vision-Language-Action Models
- Sparse Autoencoders Reveal Interpretable and Steerable Features in VLA Models
- CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
- SAM 3: Segment Anything with Concepts
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
- Inner Monologue: Embodied Reasoning through Planning with Language Models
- Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer
- NS-VLA: Towards Neuro-Symbolic Vision-Language-Action Models
- LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
- Code as Policies: Language Model Programs for Embodied Control
- ChatGPT for Robotics: Design Principles and Model Abilities
- ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
- VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
- Text2Motion: From Natural Language Instructions to Feasible Plans
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
- ARC: A Reasoning Recipe for Robot Foundation Models
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies