ForceRFT: Refining VLA Actions through Force-Guided Residual Reinforcement Learning

arXiv:2609.22840 · cs.RO · Submitted 2026-09-19 · Read on arXiv

cs.RO

Submitted: 2026-09-19

Updated: 2026-09-19

Comments: 8 pages, 4 figures, 3 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Actor — 29× in this paper · explained in 3 episodes
• Reinforcement Learning — 14× in this paper · explained in 4 episodes
• Adaptation — 12× in this paper · explained in 1 episode
• Ablation — 11× in this paper · explained in 1 episode
• Human-in-the-Loop — 4× in this paper · explained in 3 episodes
• Online Adaptation — 4× in this paper · explained in 3 episodes
• VLA Models — 4× in this paper · explained in 3 episodes
• Online Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Flow Matching — 2× in this paper · explained in 7 episodes
• Multimodal Fusion — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 4 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes

Sources

• SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
• From Foundation to Application: Improving VLA Models in Practice
• G0.5: One Autoregressive Stream for Robot Reasoning and Action
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• OpenVLA: An Open-Source Vision-Language-Action Model
• ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching
• FD-VLA: Force-Distilled Vision-Language-Action Model for Contact-Rich Manipulation
• FM-VLA: Force-based Memory for Vision-Language-Action Models in Contact-Rich Manipulation
• Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation
• FAWAM: Force-Aware World Action Models for Closed-Loop Contact-Rich Manipulation
• FAVLA: A Force-Adaptive Fast-Slow VLA model for Contact-Rich Robotic Manipulation
• ForceVLA2: Unleashing Hybrid Force-Position Control with Force Awareness for Contact-Rich Manipulation
• CompliantVLA-adaptor: VLM-Guided Variable Impedance Action for Safe Contact-Rich Manipulation
• Human-in-the-Loop Imitation Learning using Remote Teleoperation
• CRAFT: Adapting VLA Models to Contact-rich Manipulation via Force-aware Curriculum Fine-tuning
• From Imitation to Refinement -- Residual RL for Precise Assembly
• Residual Off-Policy RL for Finetuning Behavior Cloning Policies
• Residual Reinforcement Learning for Robot Control
• TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation

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