Book Image

Hands-On ROS for Robotics Programming

By : Bernardo Ronquillo Japón
Book Image

Hands-On ROS for Robotics Programming

By: Bernardo Ronquillo Japón

Overview of this book

Connecting a physical robot to a robot simulation using the Robot Operating System (ROS) infrastructure is one of the most common challenges faced by ROS engineers. With this book, you'll learn how to simulate a robot in a virtual environment and achieve desired behavior in equivalent real-world scenarios. This book starts with an introduction to GoPiGo3 and the sensors and actuators with which it is equipped. You'll then work with GoPiGo3's digital twin by creating a 3D model from scratch and running a simulation in ROS using Gazebo. Next, the book will show you how to use GoPiGo3 to build and run an autonomous mobile robot that is aware of its surroundings. Finally, you'll find out how a robot can learn tasks that have not been programmed in the code but are acquired by observing its environment. You'll even cover topics such as deep learning and reinforcement learning. By the end of this robot programming book, you'll be well-versed with the basics of building specific-purpose applications in robotics and developing highly intelligent autonomous robots from scratch.
Table of Contents (19 chapters)
1
Section 1: Physical Robot Assembly and Testing
5
Section 2: Robot Simulation with Gazebo
8
Section 3: Autonomous Navigation Using SLAM
13
Section 4: Adaptive Robot Behavior Using Machine Learning

Setting the training task parameters

At this point, we are briefly going to introduce the three essential concepts in reinforcement learning: states, actions, and rewards. In this section, we will give you minimal information so that you can understand the practical exercise in this chapter. In this case, we are applying the strategy of focus on the practice to really understand the theory.

This method of focus on the practice to really understand the theory is especially required for complex topics that are better understood if you follow an empirical approach with easy-to-run examples. This preliminary practical success should provide you with enough motivation to get deeper into the topic, a task that in any case will be hard both in the algorithms and in the mathematics behind them.

So, let's proceed to define these core concepts involved in the learning task of the robot...