Abstract
This research explores the potential of leveraging OpenAIs GPT-3.5-Turbo API for automating Arduino robot design through a structured multi-level language processing chain termed LangChain. The system breaks down the design process into six stages, from preliminary design sketching to failure analysis. Each stage generates robot design components using user inputs, progressively building upon the previous outputs. The results highlight the models capabilities in generating functional preliminary designs, suggesting hardware and software components, and offering assembly instructions. While demonstrating a commendable level of technical knowledge, the system requires further refinement in numerical analysis and design reviews. This approach provides a foundational framework for bridging the knowledge gap between amateurs and professionals in robotic design.
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