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Weekly Schedule

13-Week Course Structure​

This course is structured across 13 weeks, progressively building foundational knowledge and practical skills in physical AI and humanoid robotics. Each week introduces new concepts and builds upon previously learned material.

Course Timeline​

Week 1: Course Introduction & Physical AI​

Topics:

  • Course overview, syllabus, and project expectations
  • Introduction to Physical AI and embodied intelligence
  • Distinction between digital AI and Physical AI
  • Humanoid robotics challenges and opportunities

Activities:

  • Course orientation
  • Reading: Chapter 1 (Physical AI)
  • Discussion: Future of embodied intelligence

Deliverables:

  • None (orientation week)

Week 2: ROS 2 Core Concepts​

Topics:

  • ROS 2 architecture and distributed systems
  • Nodes and their responsibilities
  • Topics and publish-subscribe pattern
  • ROS 2 workspaces and packages

Activities:

  • Install ROS 2 environment
  • Create first ROS 2 node
  • Implement publisher and subscriber
  • Lab: Basic topic communication

Deliverables:

  • Lab report: ROS 2 communication demo

Week 3: Services, Actions & Package Development​

Topics:

  • Services for request-response communication
  • Actions for goal-oriented tasks
  • ROS 2 package structure
  • Launch files and parameters

Activities:

  • Implement service server and client
  • Create action server with feedback
  • Build complete ROS 2 package
  • Start: ROS 2 Package Project

Deliverables:

  • ROS 2 Package Project (due Week 4)

Week 4: Digital Twins & Gazebo Basics​

Topics:

  • Digital twin concepts in robotics
  • Gazebo simulation environment
  • URDF robot description format
  • Basic physics simulation

Activities:

  • Set up Gazebo environment
  • Create simple robot URDF
  • Simulate basic robot model
  • Lab: Robot visualization in Gazebo

Deliverables:

  • ROS 2 Package Project submission
  • Lab report: Gazebo simulation

Week 5: URDF/XACRO Modeling & Control​

Topics:

  • Advanced URDF features
  • XACRO macros and properties
  • Joint controllers
  • Sensor plugins in Gazebo

Activities:

  • Build humanoid robot model
  • Implement joint control
  • Add camera and IMU sensors
  • Lab: Sensor data acquisition

Deliverables:

  • Lab report: Robot modeling and control

Week 6: Unity Digital Twin Setup​

Topics:

  • Unity for robotics visualization
  • Unity-ROS 2 integration
  • High-fidelity rendering
  • Custom UI development

Activities:

  • Set up Unity Robotics Hub
  • Import URDF into Unity
  • Configure ROS 2 connection
  • Lab: Unity visualization

Deliverables:

  • Lab report: Unity integration

Week 7: Digital Twin Project Week​

Topics:

  • Advanced visualization techniques
  • Human-robot interaction in simulation
  • Project integration and testing

Activities:

  • Complete: Digital Twin Simulation Project
  • System integration
  • Testing and debugging
  • Documentation

Deliverables:

  • Digital Twin Simulation Project submission

Week 8: NVIDIA Isaac Sim Introduction​

Topics:

  • NVIDIA Isaac ecosystem overview
  • Isaac Sim setup and configuration
  • Photorealistic rendering
  • Basic robot simulation in Isaac

Activities:

  • Install Isaac Sim
  • Create first Isaac scene
  • Import robot model
  • Lab: Isaac Sim basics

Deliverables:

  • Lab report: Isaac Sim setup

Week 9: Synthetic Data & AI Training​

Topics:

  • Synthetic data generation
  • Domain randomization
  • Training vision models
  • Reinforcement learning basics

Activities:

  • Generate synthetic camera data
  • Implement domain randomization
  • Train simple perception model
  • Lab: Synthetic data pipeline

Deliverables:

  • Lab report: Synthetic data generation

Week 10: Visual SLAM Implementation​

Topics:

  • SLAM fundamentals
  • Visual SLAM algorithms
  • ORB-SLAM3 and RTAB-Map
  • Localization and mapping

Activities:

  • Configure VSLAM system
  • Test in Isaac Sim environment
  • Evaluate map quality
  • Lab: VSLAM implementation

Deliverables:

  • Lab report: VSLAM evaluation

Week 11: Nav2 for Humanoid Navigation​

Topics:

  • Nav2 architecture
  • Path planning algorithms
  • Footstep planning for humanoids
  • Dynamic obstacle avoidance

Activities:

  • Configure Nav2 for bipedal robot
  • Implement footstep planner
  • Test navigation scenarios
  • Start: Isaac Perception Pipeline Project

Deliverables:

  • Isaac Perception Pipeline Project (due Week 12)

Week 12: VLA Systems Integration​

Topics:

  • Vision-Language-Action architecture
  • OpenAI Whisper integration
  • GPT for task planning
  • Multimodal fusion

Activities:

  • Implement voice command system
  • Integrate GPT task planner
  • Test VLA pipeline
  • Start: Capstone Humanoid Project

Deliverables:

  • Isaac Perception Pipeline Project submission
  • Capstone project proposal

Week 13: Capstone Presentations​

Topics:

  • Project demonstrations
  • Peer review and feedback
  • Course wrap-up and future directions

Activities:

  • Complete: Capstone Humanoid Project
  • Final presentations (15 min each)
  • Live demonstrations
  • Course retrospective

Deliverables:

  • Capstone Humanoid Project submission
  • Final presentation
  • Demonstration video

Assessment Timeline​

WeekAssessmentWeight
4ROS 2 Package Project20%
7Digital Twin Simulation25%
12Isaac Perception Pipeline25%
13Capstone Humanoid Project30%

Weekly Time Commitment​

  • Lectures/Reading: 3-4 hours
  • Labs/Hands-on: 4-5 hours
  • Project Work: 3-4 hours
  • Total: 10-13 hours per week

Office Hours & Support​

  • Office Hours: TBD (2 hours per week)
  • Discussion Forum: Available 24/7
  • Lab Access: As per institutional schedule

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