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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

Robot perception and SLAM

The most straightforward way to implement robot navigation in ROS is by using an LDS that provides 360° coverage, allowing the robot to be aware of all the objects and obstacles around it.

In the introduction to this chapter, we identified the EAI YDLIDAR X4 as a low-cost option that can be integrated with our physical robot. That will be covered in the next chapter, while in the present one we will develop its virtual model to be integrated in Gazebo.

The next subsection extends the virtual GoPiGo3 that we've worked on in this chapter to include this very model of LDS. Afterward, we will deploy a quick SLAM example to get an overview of what this functionality can provide to robot navigation.

Adding a Laser Distance Sensor (LDS)

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