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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

Introducing robot path planning

In this section, we will be applying decision tree techniques to perform robot navigation. Some people like to refer to these as graph-based solutions, but any sort of navigation problem ends up being a decision tree. Consider as you drive your car, can you divide your navigation problems into a set of decisions – turn right, turn left, or go straight?

We are going to take what we have learned so far and press on to a problem related to classification, and that is grid searching and path finding. We will be learning about the famous and widely used A* (pronounced A-star) algorithm. This will start with grid navigation methods, topological path finding, such as GPS route finding, and finally, expert systems. You will see that these are all versions and variations on the topic of decision trees that we have already learned.

Some problems and datasets, particularly in robotics, lend themselves to a grid-based solution as a simplification of...

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