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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

Training GoPiGo3 to reach a target location while avoiding obstacles

Prior to running training in the scenario, we should note the adjustment of a parameter that dramatically affects the computational cost. This is the horizontal sampling of the LDS, since the state of the robot is characterized by the set of range values in a given step of the simulation. In previous chapters, when we performed navigation in Gazebo, we used a sampling rate of 720 for LDS. This means that we have circumferential range measurements at 1º resolution.

For this example of reinforcement learning, we are reducing the sampling to 24, which means a range resolution of 15º. The positive aspect of this decision is that you reduce the state vector from 360 items to 24, which is a factor of 15. You may have guessed that this will make the simulation more computationally efficient. In contrast, you...

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