From Observation to Action: Latent Action-based Primitive Segmentation for VLA Pre-training in Industrial Settings
We present a novel unsupervised framework to unlock vast unlabeled human demonstration data from continuous industrial video streams for Vision-Language-Action (VLA) model pre-training. Our method first trains a lightweight motion tokenizer to encode motion dynamics, then employs an unsupervised act