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Hands-On ROS for Robotics Programming

You're reading from  Hands-On ROS for Robotics Programming

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781838551308
Pages 432 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Bernardo Ronquillo Japón Bernardo Ronquillo Japón
Profile icon Bernardo Ronquillo Japón

Table of Contents (19) Chapters

Preface Section 1: Physical Robot Assembly and Testing
Assembling the Robot Unit Testing of GoPiGo3 Getting Started with ROS Section 2: Robot Simulation with Gazebo
Creating the Virtual Two-Wheeled ROS Robot Simulating Robot Behavior with Gazebo Section 3: Autonomous Navigation Using SLAM
Programming in ROS - Commands and Tools Robot Control and Simulation Virtual SLAM and Navigation Using Gazebo SLAM for Robot Navigation Section 4: Adaptive Robot Behavior Using Machine Learning
Applying Machine Learning in Robotics Machine Learning with OpenAI Gym Achieve a Goal through Reinforcement Learning Assessment Other Books You May Enjoy

Technical requirements

In this chapter, we will make use of the code in the Chapter11_OpenAI_Gym folder, located at https://github.com/PacktPublishing/Hands-On-ROS-for-Robotics-Programming/tree/master/Chapter11_OpenAI_Gym. Copy the files of this chapter to the ROS workspace, putting them inside the src folder:

$ cp -R ~/Hands-On-ROS-for-Robotics-Programming/Chapter11_OpenAI_Gym ~/catkin_ws/src/

Next, you will need to install Anaconda (https://www.anaconda.com). This is the Python distribution that has become the de facto open source standard for the Data Science community. It provides a complete Python environment for machine learning projects.

Visit the download section of the Anaconda website at https://www.anaconda.com/distribution/#linux, and select the Python 2.7 bundle. We select this package because the ROS Python client is focused on this version; however, you should be...

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