VLA Systems Glossary

This glossary contains key terms and definitions specific to Vision-Language-Action (VLA) systems covered in Module 4.

Core Terms

Vision-Language-Action (VLA) Systems : A paradigm in robotics where visual perception, natural language understanding, and action execution are tightly integrated, enabling robots to process visual and linguistic inputs jointly to generate appropriate actions.

Sense → Plan → Act : The fundamental processing flow in VLA systems where sensory inputs are processed (Sense), followed by cognitive planning (Plan), and finally action execution (Act).

Multimodal Fusion : The process of combining information from multiple sensory modalities (e.g., vision and language) to create a unified understanding of the environment and task requirements.

Large Language Models (LLMs) in Robotics : Advanced AI models that process natural language commands and translate them into robotic action sequences, serving as the cognitive layer in VLA systems.

Embodied AI : Artificial intelligence that is situated in a physical or simulated environment and can interact with that environment through sensing and acting.

Natural Language to Action Mapping : The process of translating high-level natural language commands into low-level robotic control signals or action sequences.

Perception-Action Coupling : The tight integration between perceptual processing and action generation, where actions influence perception and perception guides actions in a continuous loop.

End-to-End Learning in Robotics : Training approaches where the entire system from sensory input to motor output is learned jointly, rather than as separate components.

Technical Terms

OpenAI Whisper : A speech recognition model used to convert spoken language into text for further processing in voice-to-action pipelines.

ROS 2 Actions : The standard mechanism in ROS 2 for communicating long-running tasks between nodes, commonly used for robot command execution.

Cross-Modal Attention : A mechanism in neural networks that allows information from one modality (e.g., vision) to influence processing in another modality (e.g., language).

Visuomotor Control : The control of robot actions based on visual input, often combined with other sensory modalities and high-level commands.

Task Decomposition : The process of breaking down high-level natural language tasks into sequences of lower-level, executable actions.

Grounded Language Understanding : Natural language processing that connects linguistic expressions to perceptual experiences and physical actions in the environment.