RAPID: Robot Agentic Programming from Demonstrations

arXiv:2609.30249 · cs.RO, cs.AI, cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.RO, cs.AI, cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Project page: https://yuyaoliu.me/projects/rapid

Terminology

• Verification — 18× in this paper · explained in 2 episodes
• Generalization — 10× in this paper · explained in 13 episodes
• Agentic Coding — 8× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Agentic Loop — 3× in this paper · explained in 1 episode
• Motion Primitives — 3× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Action Primitives — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes

Sources

• GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
• ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
• ASPIRE: Agentic /Skills Discovery for Robotics
• AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation
• LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
• RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks
• Playful Agentic Robot Learning
• Rational Inverse Reasoning: Few-Shot Imitation by Inferring Intent through Planning
• $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

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