Chapter 0: Foundations

The Vision-Language-Action (VLA) stack represents the fundamental architecture for building intelligent robotic systems that can perceive, reason, and act in the physical world.

The Core Problem

Given:

  • Scene encoding (visual perception)
  • Natural language instruction (task specification)

Find:

  • Action sequence (robot control)

Textbook Structure

This living textbook covers the complete VLA pipeline across 8 chapters:

  1. Foundations - Core concepts and problem formulation
  2. Architectures - Model designs and network topologies
  3. Data - Dataset construction and curation strategies
  4. Training - Optimization and fine-tuning methods
  5. Evaluation - Metrics and benchmarking protocols
  6. Deployment - Production systems and scaling
  7. Applications - Real-world use cases and case studies
  8. Future Directions - Open problems and research frontiers

Each chapter builds on rigorous validation principles and real-world deployment constraints.