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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

Technical requirements

We require the Robot Operating System Version 2 (ROS 2) for this chapter. This book uses the Foxy Fitzroy release: http://wiki.ros.org/foxy/Installation. This chapter assumes that you have completed Chapter 6, where we gave the robot a voice and the ability to receive voice commands. We will be using the Mycroft interface and voice text-to-speech system, which is called Mimic: https://github.com/MycroftAI/mimic3. You’ll find the code for this chapter in the GitHub repository for this book at https://github.com/PacktPublishing/Artificial-Intelligence-for-Robotics-2e.

We will also be using the Keras library for Python (https://keras.io), which is a powerful library for machine learning applications and lets us build custom neural networks. You can install it using the following command:

pip install keras

You will also need PyTorch, which is installed with this command:

pip3 install torch torchvision torchaudio --index-url https://download.pytorch...
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