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Artificial Intelligence for Robotics

You're reading from   Artificial Intelligence for Robotics Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129592
Length 344 pages
Edition 2nd Edition
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Author (1):
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Francis X. Govers III Francis X. Govers III
Author Profile Icon Francis X. Govers III
Francis X. Govers III
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Building Blocks for Robotics and Artificial Intelligence
2. Chapter 1: The Foundation of Robotics and Artificial Intelligence FREE CHAPTER 3. Chapter 2: Setting Up Your Robot 4. Chapter 3: Conceptualizing the Practical Robot Design Process 5. Part 2: Adding Perception, Learning, and Interaction to Robotics
6. Chapter 4: Recognizing Objects Using Neural Networks and Supervised Learning 7. Chapter 5: Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms 8. Chapter 6: Teaching a Robot to Listen 9. Part 3: Advanced Concepts – Navigation, Manipulation, Emotions, and More
10. Chapter 7: Teaching the Robot to Navigate and Avoid Stairs 11. Chapter 8: Putting Things Away 12. Chapter 9: Giving the Robot an Artificial Personality 13. Chapter 10: Conclusions and Reflections 14. Answers 15. Index 16. Other Books You May Enjoy Appendix

Teaching the Robot to Navigate and Avoid Stairs

Let’s have a quick review of our quest to create a robot that picks up toys. We’ve created a toy detector and trained the robot arm. What’s next on our to-do list? We need to drive the robot to the location of the toy in order to pick it up. That sounds important.

This chapter covers navigation and path planning for our toy-grabbing robot helper. You have to admit that this is one of the most difficult problems in robotics. There are two parts to the task – figuring out where you are (localization), and then figuring out where you want to go (path planning). Most robots at this point would be using some sort of simultaneous localization and mapping (SLAM) algorithm that would first map the room, and then figure out where the robot is within it. But is this really necessary? First of all, SLAM generally requires some sort of 3D sensor, which we don’t have, and a lot of processing, which we don’...

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