Chapter 4: Course Overview
Overview
This chapter maps the complete 13-week learning journey from foundational concepts through capstone project.
Estimated Time: 3 hours
Course Structure
Weekly Progression
Weeks 1-2: Foundations (Part I)
- Physical AI concepts
- Humanoid landscape
- Sensor foundations
- Milestone: Understanding of embodied intelligence
Weeks 3-5: ROS 2 (Part II)
- ROS 2 architecture
- Python development
- URDF modeling
- Control systems
- Milestone: Working ROS 2 nodes and robot model
Weeks 6-7: Simulation (Part III)
- Gazebo setup and operation
- Humanoid simulation
- Unity visualization
- Milestone: Simulated walking humanoid
Weeks 8-9: NVIDIA Isaac (Part IV)
- Isaac Sim introduction
- Perception and synthetic data
- Isaac ROS integration
- Nav2 navigation
- Milestone: Autonomous navigation in Isaac Sim
Weeks 10-11: VLA Systems (Part V)
- VLA concepts
- Whisper voice recognition
- LLM task planning
- Multimodal interaction
- Milestone: Voice-controlled robot commands
Week 12: Hardware (Part VI)
- Workstation setup
- Jetson deployment
- Robot platform selection
- Cloud infrastructure
- Milestone: Edge deployment working
Weeks 13-15: Capstone (Part VII)
- System architecture design
- Full integration
- Sim-to-real transfer
- Testing and evaluation
- Milestone: Voice-driven autonomous humanoid
Learning Outcomes
By course end, you will:
- Design and implement ROS 2 robot systems
- Simulate humanoids in Gazebo and Isaac Sim
- Integrate voice and language models for control
- Deploy AI models to edge devices (Jetson)
- Transfer learned policies from simulation to hardware
Assessment Strategy
- Labs (40%): Weekly hands-on exercises
- Midterm Project (25%): ROS 2 + Simulation integration
- Final Capstone (30%): Complete voice-controlled system
- Participation (5%): Discussions and peer review
Next Steps
➡️ Begin Part II: ROS 2