Skip to main content

Module 3: Perception for Physical AI

Overview​

Welcome to Module 3 of the Physical AI & Humanoid Robotics textbook. In this module, you'll explore the critical field of robot perception - how robots understand and interpret their environment. Perception is fundamental to creating embodied AI systems that can interact effectively with the physical world.

Learning Path​

This module is organized into three comprehensive chapters that build upon each other:

  1. Introduction to Robot Perception - Understand the foundational concepts of how robots perceive their environment and the various sensor modalities available
  2. Vision Systems: Cameras & Depth Sensing - Master camera-based perception and depth sensing technologies for robotics applications
  3. Sensor Fusion for Embodied Intelligence - Learn to combine multiple sensor inputs for robust perception in real-world environments

What You'll Learn​

By the end of this module, you will be able to:

  • Explain fundamental perception concepts and their importance in robotics
  • Implement camera-based perception systems using various techniques
  • Work with depth sensing technologies and RGB-D sensors
  • Apply sensor fusion techniques to combine multiple sensor inputs
  • Create robust perception systems that handle uncertainty and environmental challenges
  • Design perception pipelines that integrate with your AI and control systems

Prerequisites​

This module builds upon concepts from Module 1 (The Robotic Nervous System - ROS 2) and Module 2 (The Digital Twin). A basic understanding of robotics concepts and the ROS 2 framework will be helpful as you progress through the perception techniques covered in this module.

Getting Started​

Begin with Chapter 1: Introduction to Robot Perception to understand the foundational concepts of robot perception in physical AI applications.