AI Control Systems: Prototyping Autonomous Robots with Text Prompts

Modern AI models excel at generating text, but how do you use that capability to manage and control real-world physical systems or robots? This course teaches you the foundational steps for connecting large language models (LLMs) to control loops, allowing you to prototype complex autonomous behaviors in a simulated environment using only high-level text commands.What you'll learn: Understand the fundamental architecture for using LLMs as control agents. Apply prompt engineering techniques specifically for generating functional control code and action sequences. Configure an open-source simulation environment to model a physical system and its available actions. Practice implementing basic tool use and function calling patterns to interface the LLM with the simulator API. Design simple autonomous behaviors, translating text prompts into validated robot actions. We start by defining key terminology and exploring the necessary open-source components. The course then moves through practical exercises, focusing on writing effective prompts and implementing the control interface logic necessary to run your first autonomous prototype. This course is designed for beginners interested in the intersection of AI, robotics, and control systems. No prior experience with advanced AI modeling or complex robotics is required, only basic programming knowledge. Start building the future of autonomous control today.