Chapter 0: Math Basics

Mathematical Foundation

Robotics heavily relies on a robust mathematical foundation. To succeed in this course, familiarity with the following areas is recommended:

  • Trigonometry: Fundamental for analyzing angles, rotations, and transformations in robotic systems.

  • Linear Algebra: Essential for understanding robotic motion, kinematics, and system modeling.

  • Calculus: Used extensively for analyzing dynamics, motion planning, and control.

  • Probability and Statistics: Critical for interpreting sensor data, uncertainty modeling, and robotics perception.

You can find links to external resources for these basic mathematical foundations in the Basic Maths Foundations Page.

Additionally, Robotics relies also on:

  • Optimization: Important for control strategies, path planning, AI and machine learning for robot learning, and decision-making in robotics. You can find a brief introduction to optimization in the Optimization chapter.

  • Graph Theory: Important for motion planning and many AI algorithms for robot learning. You can find a brief introduction to Graph Theory in the Graph theory chapter.

  • 0.0 Math Basics

  • 0.1 Optimization

  • 0.2 Graph Theory

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