Book Modules
Module 1: Nervous System
ROS 2 fundamentals, URDF, sensors, and robot nervous system architecture.
Module 2: Digital Twin
Unity simulation, Gazebo environments, and digital twin technologies.
Module 3: AI Brain
Cognitive architectures, planning algorithms, and AI reasoning systems.
Module 4: Vision-Language-Action
VLA systems, multimodal perception, and human-robot interaction.
Weekly Curriculum Breakdown
Weeks 1-2: Introduction to Physical AI
- Physical AI Foundations: Understanding convergence of AI with physical systems
- Embodied Intelligence: Intelligence from environment interaction
- Humanoid Robotics Landscape: Current state-of-the-art overview
- Sensor Systems: LIDAR, cameras, IMUs, force/torque sensors
Weeks 3-5: ROS 2 Fundamentals
- ROS 2 Architecture: Nodes, topics, services, and actions
- Package Development: Building ROS 2 packages with Python
- Launch Files: Parameter management and system configuration
- Communication Patterns: Different paradigms in ROS 2
Weeks 6-7: Robot Simulation with Gazebo
- Gazebo Environment: Setting up simulation environments
- URDF/SDF Formats: Robot description and simulation formats
- Physics Simulation: Accurate physics modeling and sensor simulation
- Unity Integration: Advanced visualization using Unity
Weeks 8-10: NVIDIA Isaac Platform
- Isaac SDK: NVIDIA Isaac development platform for AI robotics
- Isaac Sim: High-fidelity simulation environment
- Perception and Manipulation: AI-powered capabilities
- Reinforcement Learning: Learning-based approaches for control
- Sim-to-Real Transfer: Techniques for simulation-to-reality transfer
Weeks 11-12: Humanoid Robot Development
- Kinematics and Dynamics: Understanding robot movement and balance
- Bipedal Locomotion: Walking and balance control
- Manipulation and Grasping: Using humanoid hands for interaction
- Human-Robot Interaction: Natural interaction design
Week 13: Conversational Robotics
- Conversational AI: Integrating GPT models for interaction
- Speech Recognition: Processing spoken commands
- Multi-Modal Interaction: Combining speech, gesture, and vision
Course Structure
This comprehensive 13-week curriculum takes you from foundational concepts to advanced humanoid robotics, covering everything from ROS 2 fundamentals to conversational AI integration.
Learning Path
Progress from understanding physical AI fundamentals to implementing sophisticated humanoid robot systems with AI-powered perception, planning, and interaction capabilities.
Key Concepts
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Physical AI Fundamentals
- Physical AI: Convergence of AI with physical systems
- Embodied Cognition: Intelligence from environment interaction
- Sim-to-Real Transfer: Simulation before real-world deployment
- Perception-Action Loops: Sensing, processing, and acting cycles
- Safety-First Design: Prioritizing safety in AI integration
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Core Technologies
- ROS 2: Middleware for robotic system communication
- URDF: Robot model description format
- Digital Twins: Virtual replicas of physical systems
- Behavior Trees: Structured robotic behavior organization
- SLAM: Simultaneous Localization and Mapping
🤖
AI Integration
- Vision-Language-Action: Unified perception and action
- LLM Integration: Large language models for planning
- Sensor Fusion: Combining multiple sensor data
- Cognitive Architecture: Robot reasoning frameworks
- Multi-Modal Planning: Spatial, temporal, and resource planning
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Applications
- Autonomous Systems: Self-driving vehicles and drones
- Humanoid Robotics: Human-like assistance and collaboration
- Industrial Automation: Smart manufacturing systems
- Healthcare Robotics: Medical assistance devices
- Service Robotics: Domestic and commercial robots