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Duration 14 hours
Course Outline
Overview of Physical AI
- Definition and scope of Physical AI
- Core elements: hardware, software, and artificial intelligence
- Practical applications of Physical AI in operational contexts
Fundamentals of Robotics
- Essential concepts in robotics and automation
- Overview of sensors, actuators, and control mechanisms
- Introduction to the Robot Operating System (ROS)
Artificial Intelligence Algorithms for Physical Systems
- Machine learning and perception techniques for robotics
- Path planning and navigation fundamentals
- Introduction to decision-making processes and system control
Prototyping and Construction of Intelligent Systems
- Selection of appropriate hardware: Arduino, Raspberry Pi, and equivalent platforms
- Integration of sensors and actuators
- Assembly and testing of a basic AI-driven robotic system
Practical Exercises
- Configuration of a basic ROS environment
- Development of a line-following robot
- Implementation of a basic obstacle avoidance mechanism
Deployment and Field Testing
- Debugging and troubleshooting of robotic systems
- Conducting field trials of prototypes
- Performance analysis and iterative design refinement
Challenges and Emerging Trends
- Scaling from prototype stages to full-scale systems
- Ethical frameworks and safety protocols in Physical AI
- Emerging technologies and innovative developments
Conclusion and Subsequent Actions
Requirements
- Basic programming proficiency (Python recommended)
- Interest in robotics and artificial intelligence
Audience
- AI developers
- Technology professionals
- STEM students
