The Full Stack of Physical AI: Simulation, Foundation Models, and Edge Deployment for Next-Generation Robotics Applications

Physical AI systems, including robotics and autonomous platforms, require tightly integrated pipelines spanning data collection, model training, and real-time deployment. This tutorial presents a full-stack perspective on building such systems, covering simulation-based data generation, foundation models for robot control, and deployment on edge hardware. It introduces practical workflows using modern tools for human-in-the-loop data collection, multimodal robot foundation models, and hardware-aware optimization for low-latency inference. The tutorial further highlights challenges in scaling and deploying physical AI systems, providing attendees with actionable guidance and open-source resources for end-to-end robotics development.