Introduction to Physical AI: Building Intelligent Machines

• Basic programming knowledge (Python recommended)
• Interest in robotics and artificial intelligence

Audience

• AI developers
• Tech enthusiasts
• STEM students

Physical AI merges artificial intelligence with robotics to create intelligent machines capable of interacting with the physical world. This cutting-edge field combines hardware prototyping, AI algorithms, and real-world applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level participants who wish to explore the fundamentals of Physical AI, including its components, development process, and hands-on implementation of basic intelligent machines.

By the end of this training, participants will be able to:

• Understand the principles and potential applications of Physical AI.
• Design and prototype simple AI-powered robotic systems.
• Implement basic AI algorithms for machine perception and decision-making.
• Navigate and use tools like ROS for robotics development.
• Integrate hardware and software to build functional intelligent machines.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Physical AI

• What is Physical AI?
• Key components: hardware, software, and AI
• Applications of Physical AI in real-world scenarios

Foundations of Robotics

• Basic concepts in robotics and automation
• Overview of sensors, actuators, and controllers
• Introduction to Robot Operating System (ROS)

AI Algorithms for Physical Systems

• Machine learning and perception for robotics
• Path planning and navigation basics
• Introduction to decision-making and control

Prototyping and Building Intelligent Machines

• Choosing the right hardware: Arduino, Raspberry Pi, and others
• Integrating sensors and actuators
• Building and testing a simple AI-powered robotic system

Hands-On 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 iterating on design

Challenges and Future Trends

• Scaling up from prototypes to full systems
• Ethical and safety considerations in Physical AI
• Emerging technologies and innovations

Summary and Next Steps