Robotics Perception: A Tutorial Introduction

A comprehensive tutorial on robotics perception using Python's scientific computing libraries.

Overview

This tutorial provides a complete introduction to robotics perception, covering fundamental concepts through advanced topics, all implemented using Python's standard scientific computing libraries (numpy, scipy, matplotlib). Unlike other robotics perception resources that rely on specialized libraries like GTSAM, this tutorial focuses on understanding the underlying mathematical principles by implementing everything from scratch.

Table of Contents

1. Introduction and Motivation
2. Mathematical Foundations
3. Sensors and Sensor Models
4. Filtering and Estimation Theory
5. Localization
6. Mapping
7. SLAM
8. Advanced Perception Algorithms

Prerequisites

• Basic knowledge of Python programming
• Understanding of linear algebra and probability theory
• Familiarity with calculus

Installation

pip install -r requirements.txt

Usage

Each chapter contains:

• Theoretical background with mathematical derivations
• Modular code examples organized by topic
• Visual figures and plots
• Exercises and hands-on activities

Running Examples

Navigate to the desired chapter directory and run the example scripts:

cd chapters/01_introduction
python examples/simple_motion.py

Chapter Structure

Each chapter is organized as follows:

• README.md - Chapter overview and file organization
• [chapter].md - Main theoretical content with embedded figures
• examples/ - Modular code examples by topic
• figures/ - Generated plots and visualizations

Dependencies

This tutorial uses only standard scientific Python libraries:

• numpy: Numerical computations
• scipy: Scientific computing
• matplotlib: Visualization
• PIL/Pillow: Image processing (for computer vision examples)

Learning Path

1. Beginner: Start with chapters 1-3 to understand fundamentals
2. Intermediate: Continue with chapters 4-6 for core perception algorithms
3. Advanced: Complete chapters 7-8 for complex integration topics

Contributing

This is an educational resource. Feel free to suggest improvements or report issues.

License

This tutorial is provided for educational purposes.