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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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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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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

Deep learning applied to robotics – computer vision

The practical part of this chapter consists of operationally implementing the ML node described earlier. What we represented there as a black box is developed now as a ROS package that you may integrate with the functionalities you discovered in previous chapters:

  • The remote control in Chapter 7, Robot Control and Simulation, for both the virtual robot in Gazebo and the physical GoPiGo3
  • Robot navigation for a virtual robot in Chapter 8, Virtual SLAM and Navigation Using Gazebo, and the physical GoPiGo3 in Chapter 9, SLAM for Robot Navigation

So, we divide this section into two parts:

  • The first section, Object recognition in Gazebo, provides you with the tools to integrate the ML node for image recognition in Gazebo so that, after finishing the practice, you may let your creativity fly to combine object recognition with...
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