Introduction

I always find robotics a fascinating subject but hard to learn on my own. There are many reasons why learning robotics is hard. For one thing, robotics systems are complex. To control even a single part of a robotics system demands tremendous domain knowledge. That's why in robotics companies, we typically see teams dedicated to a very specific domain.

The very nature of the field of robotics makes self-learning challenging. To understand how to control a robotic arm, we need to understand coordinate systems, linear applications, control theories, and of course physics. For someone who has left the school and no longer deals with these things on a daily basis, even reviewing these concepts can be a time-consuming endeavor.

Perhaps the greatest obstacle is the constant friction caused by context switches when learning robotics. For example, to understand how a robotic arm is controlled, one has to go back to refresh the memory on linear algebra, angular momentum, PID controller, and more. While it's fun to review these concepts, it often becomes distracting and sometimes a little annoying.

After a while, I finally realized that the real pain point is that this knowledge is scattered all over the place. Yes, there are tons of videos explaining the PID controller, but it takes a good amount of time to find one that explains the concept in a way that anyone can understand. Yes, there are books on linear algebra and probabilities, but no one can afford to read a whole probability book just to understand how SLAM works.

What if there is a book that covers the fundamentals and offers a high-level overview of the subject?

This book starts with introducing ROS2 and Gazebo, a set of software libraries and tools that are useful for building robot applications and simulations. It then progresses to a chapter dedicated to robotics programming as solid programming skills is key to the success of robotic projects. In the second part, the book shifts its focus to the theoretical aspect of robotics. Reviews of relevant Mathematics and Physics are provided. Additionally, the book features in-depth chapters on control theory and probabilistic robotics, essential to any robotic applications.