PhysicalAI

π₀ is an innovative VLA model that combines a vision–language backbone with an action expert module and flow matching, producing continuous action sequences from natural language and images.

Diffusion-based models such as DDPM and their use in policy learning rely on denoising mechanisms, UNet architectures, and structured action representations to capture complex sequential behaviors.

OpenVLA is a 7B open-source VLA model built on Llama2 + DINOv2 + SigLIP, trained on 970k demos, achieving stronger generalization and robustness than closed RT-2-X (55B) and outperforming Diffusion Policy.

Action Chunking with Transformers (ACT) combines the representational strength of autoencoders with the contextual modeling of transformers, producing compact latent variables that generate coherent action sequences.