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Mastering ROS 2 for Robotics Programming

You're reading from   Mastering ROS 2 for Robotics Programming Design, build, simulate, and prototype complex robots using the Robot Operating System 2

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Product type Paperback
Published in Jul 2025
Publisher Packt
ISBN-13 9781836209010
Length 576 pages
Edition 4th Edition
Concepts
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Authors (2):
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Lentin Joseph Lentin Joseph
Author Profile Icon Lentin Joseph
Lentin Joseph
Jonathan Cacace Jonathan Cacace
Author Profile Icon Jonathan Cacace
Jonathan Cacace
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Toc

Table of Contents (22) Chapters Close

Preface
1. Part I: ROS 2 Programming and Simulation
2. Introduction to ROS 2 FREE CHAPTER 3. Getting Started with ROS 2 Programming 4. Implementing ROS 2 Concepts 5. Working with Robot 3D Modeling in ROS 2 6. Simulating Robots in a Realistic Environment 7. Part II: ROS 2 Applications: Navigation, Manipulation, and Control
8. Controlling Robots Using the ros2_control Package 9. Implementing ROS 2 Applications Using BehaviorTree.CPP 10. ROS 2 Navigation Stack: Nav2 11. Robot Manipulation Using MoveIt 2 12. Working with ROS 2 and Perception Stack 13. Part III: Advanced Applications and Machine Learning
14. Aerial Robotics and ROS 2 15. Designing and Programming a DIY Mobile Robot from Scratch 16. Testing, Continuous Integration, and Continuous Deployment with ROS 2 17. Interfacing Large Language Models with ROS 2 18. ROS 2 and Deep Reinforcement Learning 19. Implementing ROS 2 Visualization and Simulation Plugins 20. Other Books You May Enjoy
21. Index

LLMs for robotics

LLMs are large, deep-learning models trained on vast amounts of data. Their main component is the transformer model neural network [1].

A transformer model is a neural network that can learn the context and meaning of a sentence by tracking the relationship in sequential data, such as words, using a mathematical technique called attention. In simple words, transformers can learn and generate human-like text by analyzing patterns from large text data.

Google introduced attention in 2017 as a research paper, Attention is All You Need [2], and it is now the foundation model for all the famous LLMs like ChatGPT from OpenAI, Llama from Facebook, and Gemini from Google. These LLMs are great performers in understanding natural language, reasoning, and decision-making. Along with LLMs, there are:

  • Vision language models (VLMs), which combine an LLM with a vision encoder, enabling the LLM to understand images and videos that can be used for robot perception...
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