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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

Image manipulation

So, now that we have an image, what can we do with it? You have probably played with Adobe Photoshop or some other image manipulation program such as GIMP, and you know that there are hundreds of operations, filters, changes, and tricks you can perform on images. For instance, can make an image brighter or darker by adjusting the brightness. We can increase the contrast between the white parts of the image and the dark parts. We can make an image blurry, usually by applying a Gaussian blur filter. We can also make an image sharper (somewhat) by using a filter such as an unsharp mask. You can also use an edge detector filter, such as the Canny filter, to isolate the edges of an image, where color or value changes. We will be using all of these techniques to help the computer identify images:

Figure 4.2 – Various convolutions applied to an image

Figure 4.2 – Various convolutions applied to an image

By performing these manipulations, we want the computer to not have the computer software...

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