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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

Interfacing Large Language Models with ROS 2

This chapter will explore the possibilities of using GenAI in robotics by interfacing different large language models (LLMs) into ROS 2 by building AI agents. LLMs are a subset of GenAI mainly focused on generating text. So why does interfacing LLMs and AI agents with ROS 2 robots matter? Using LLMs and agents, robots can understand user input and generate an intelligent response. Users can use text, images, and voice as input, making the robot capable of answering questions intelligently. Other than interaction, LLM-based AI agents can control a robot by generating corresponding actions for the robot based on user input.

In this chapter, we’re going to cover the following main topics:

  • LLMs for robotics
  • Integrating ROS 2 robots with LLM agents
  • Creating ROS 2 AI agents
  • Popular ROS 2 AI agent projects
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