Discover, Learn, and Reinforce: Scaling Vision-Language-Action Pretraining with Diverse RL-Generated Trajectories

Understand

Scaling vision-language-action (VLA) model pre-training requires large volumes of diverse, high-quality manipulation trajectories.

• Most current data is obtained via human teleoperation, which is expensive and difficult to scale.
• Reinforcement learning (RL) methods learn useful skills through autonomous exploration, making them a viable approach for generating data.
• However, standard RL training collapses to a narrow execution pattern, limiting its utility for large-scale pre-training.