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Hands-On ROS for Robotics Programming

You're reading from   Hands-On ROS for Robotics Programming Program highly autonomous and AI-capable mobile robots powered by ROS

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781838551308
Length 432 pages
Edition 1st Edition
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Concepts
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Author (1):
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Bernardo Ronquillo Japón Bernardo Ronquillo Japón
Author Profile Icon Bernardo Ronquillo Japón
Bernardo Ronquillo Japón
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: Physical Robot Assembly and Testing
2. Assembling the Robot FREE CHAPTER 3. Unit Testing of GoPiGo3 4. Getting Started with ROS 5. Section 2: Robot Simulation with Gazebo
6. Creating the Virtual Two-Wheeled ROS Robot 7. Simulating Robot Behavior with Gazebo 8. Section 3: Autonomous Navigation Using SLAM
9. Programming in ROS - Commands and Tools 10. Robot Control and Simulation 11. Virtual SLAM and Navigation Using Gazebo 12. SLAM for Robot Navigation 13. Section 4: Adaptive Robot Behavior Using Machine Learning
14. Applying Machine Learning in Robotics 15. Machine Learning with OpenAI Gym 16. Achieve a Goal through Reinforcement Learning 17. Assessment 18. Other Books You May Enjoy

An introduction to OpenAI Gym

In the previous chapter, we provided a practical overview of what you can expect in RL when applied to robotics. In this chapter, we will provide a general view in which you will discover how RL is used to train smart agents.

First, we will need to install OpenAI Gym and OpenAI ROS on our laptop in preparation for the practical examples. Then, we will explain its concepts.

Installing OpenAI Gym

As we did in the previous chapter, we are going to create a virtual environment for the Python setup of this chapter, which we will call gym. The following two commands allow for the creation and then the activation of gym:

$ conda create -n gym pip python=2.7
$ conda activate gym

Following this, install...

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