Chapter 7: Future Directions

Core Questions

• What are the fundamental limitations of current VLA systems?
• What breakthroughs are needed for general-purpose robots?
• How will VLA systems evolve over the next decade?

Topics

7.1 Unsolved Technical Challenges

• Long-horizon task planning
• Efficient exploration and learning
• Compositional generalization
• Physical common sense reasoning

7.2 Scaling Laws for Robotics

• Data scaling vs. model scaling
• Emergent capabilities in robot learning
• The path to foundation models for robotics
• Hardware-software co-design

7.3 Theoretical Foundations

• Formal verification for learned policies
• Sample complexity bounds
• Sim-to-real transfer theory
• Causality and interventional reasoning

7.4 Societal and Ethical Considerations

• Safety and reliability standards
• Job displacement and economic impact
• Privacy and surveillance concerns
• Environmental sustainability

7.5 Emerging Paradigms

• Embodied multi-agent systems
• Continual learning in open worlds
• Self-supervised robotic learning
• Neurosymbolic approaches

7.6 Research Agenda

• High-impact open problems
• Underexplored directions
• Interdisciplinary opportunities
• Building the robotics research community