How Visual-Language-Action (VLA) Models Work

Visual-Language-Action (VLA) models provide a framework for robots to understand visual and language commands in order to perform physical tasks. These models are built upon foundational concepts like transformers, representation learning, and imitation learning from expert demonstrations. The core of a VLA is a conditioned policy that maps observations and language instructions to a sequence of actions. Different strategies exist for generating these actions, including discretizing the continuous action space into tokens that a language model can predict.