R cubed: Training Robots to Reason in Natural Language via Reinforcement Learning
cs.RO, cs.AI, cs.CL, cs.LG
Submitted: 2026-08-26
Updated: 2026-08-26
Project page: https://robotic-reasoner.github.io
Terminology
Sources
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
- Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols
- GR-3 Technical Report
- Training Strategies for Efficient Embodied Reasoning
- See, Think, Confirm: Interactive Prompting Between Vision and Language Models for Knowledge-based Visual Reasoning
- Self-Correcting Code Generation Using Small Language Models
- Action-Free Reasoning for Policy Generalization
- RACER: Rich Language-Guided Failure Recovery Policies for Imitation Learning
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation
- PaLM-E: An Embodied Multimodal Language Model
- Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control
- Step-CoT: Stepwise Visual Chain-of-Thought for Medical Visual Question Answering
- MolmoAct2: Action Reasoning Models for Real-world Deployment
- ProcVLM: Learning Procedure-Grounded Progress Rewards for Robotic Manipulation
- SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarios
- Integrated Task and Motion Planning
- RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction
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