Vision-Language-Action Model

A Vision-Language-Action Model is a multimodal AI model that integrates visual perception, language understanding, and physical action for embodied AI tasks.

• AKA: VLA Model, Vision-Language-Action (VLA) Model, Multimodal Action Model, Embodied Language Model.
• Context:
  • It can typically process Visual Inputs including camera feeds, depth maps, and object detections.
  • It can typically understand Natural Language Instructions for task specification and goal definition.
  • It can typically generate Robot Actions through motor commands and trajectory planning.
  • It can often enable Real-Time Control through low-latency inference and continuous adaptation.
  • It can often support Multi-Task Learning across manipulation tasks, navigation tasks, and interaction tasks.
  • It can often integrate with Reinforcement Learning for policy optimization and reward modeling.
  • It can range from being a Simple Pick-and-Place Model to being a Complex Dexterous Manipulation Model, depending on its action complexity.
  • It can range from being a Single-Modal Input Model to being a Full-Multimodal Model, depending on its sensory integration.
  • It can range from being a Reactive Control Model to being a Predictive Planning Model, depending on its temporal horizon.
  • It can range from being a Task-Specific Model to being a General-Purpose Model, depending on its capability scope.
  • ...
• Examples:
  • Google Vision-Language-Action Models, such as:
    • RT-1 Model for robotic transformer.
    • RT-2 Model for vision-language-action.
    • Gemini Robotics Model for advanced manipulation.
  • Academic Vision-Language-Action Models, such as:
    • CLIP-based VLA Model for visual grounding.
    • Flamingo VLA Model for few-shot learning.
  • Commercial Vision-Language-Action Models, such as:
    • Tesla FSD Model for autonomous driving.
    • Boston Dynamics Model for dynamic locomotion.
  • ...
• Counter-Examples:
  • Vision-Only Model, which lacks action generation.
  • Language-Only Model, which lacks visual perception.
  • Pure Reinforcement Learning Model, which lacks language grounding.
• See: Multimodal Model, Robotics Model, Embodied AI Model, AI World Model, Genie World Model, Intuitive Physics Understanding Task, Hybrid AI Model, Transformer Model, Computer Vision Model.

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