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Course Outline
Introduction to Physical AI
- Defining Physical AI
- Core components: hardware, software, and AI
- Real-world applications of Physical AI
Foundations of Robotics
- Fundamental concepts in robotics and automation
- Overview of sensors, actuators, and controllers
- Introduction to the Robot Operating System (ROS)
AI Algorithms for Physical Systems
- Machine learning and perception in robotics
- Basics of path planning and navigation
- Introduction to decision-making and control mechanisms
Prototyping and Building Intelligent Machines
- Selecting appropriate hardware: Arduino, Raspberry Pi, and others
- Integrating sensors and actuators
- Constructing and testing a simple AI-driven robotic system
Practical Activities
- Setting up a basic ROS environment
- Developing a line-following robot
- Implementing a basic obstacle-avoidance system
Deployment and Real-World Testing
- Debugging and troubleshooting robotic systems
- Field-testing prototypes
- Analyzing performance and refining designs
Challenges and Future Trends
- Scaling from prototypes to complete systems
- Ethical and safety considerations in Physical AI
- Emerging technologies and innovations
Summary and Next Steps
Requirements
- Foundational programming knowledge (Python is recommended)
- Interest in robotics and artificial intelligence
Target Audience
- AI developers
- Technology enthusiasts
- STEM students
14 Hours
