Summary
This chapter explored the integration of LLMs with ROS 2, highlighting their potential to enhance robotics through natural language interaction, autonomous decision-making, and intelligent control. It introduced LLMs, VLMs, and ALMs, explaining their relevance to robotics. The chapter covered key applications, including natural language-based robot control, autonomous navigation, perception, task planning, and error diagnosis. It then detailed the integration of AI agents with ROS 2 using frameworks such as LangChain and AutoGen, providing an architecture for AI agents interacting with robots. Several ROS 2 AI agent projects were discussed, demonstrating turtlesim, Nav2, and MoveIt2 implementations. The chapter concluded with an overview of ROS 2 AI projects such as ROSA, RAI, ROS-LLM, and NVIDIA’s ROS2-NanoLLM.
The next chapter will discuss how we can apply deep reinforcement learning in ROS 2.
