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Course Outline
Introduction to Physical AI
- Defining Physical AI
- Core elements: hardware, software, and AI
- Practical applications of Physical AI in real-world settings
Fundamentals of Robotics
- Basic principles of robotics and automation
- An overview of sensors, actuators, and controllers
- Introduction to the Robot Operating System (ROS)
AI Algorithms for Physical Systems
- Machine learning and perception techniques in robotics
- Basics of path planning and navigation
- Introduction to decision-making and control logic
Prototyping and Construction of Intelligent Machines
- Selecting appropriate hardware, such as Arduino and Raspberry Pi
- Integrating sensors and actuators
- Assembling and testing a basic AI-powered robotic system
Practical Activities
- Setting up a fundamental ROS environment
- Creating a line-following robot
- Developing a basic obstacle-avoidance mechanism
Deployment and Real-World Validation
- Debugging and troubleshooting robotic systems
- Conducting field tests on prototypes
- Evaluating performance and refining the design
Challenges and Future Directions
- Scaling from prototypes to full-scale systems
- Ethical and safety aspects in Physical AI
- Emerging technologies and innovations
Summary and Subsequent Steps
Requirements
- Fundamental programming skills (Python is highly recommended)
- A keen interest in robotics and artificial intelligence
Target Audience
- AI developers
- Technology enthusiasts
- STEM students
14 Hours
