Programming Manufacturing Robots with Imperfect AI: LLMs as Tuning Experts for FDM Print Configuration Selection
The research investigates using Large Language Models (LLMs) as constrained decision modules within a Bayesian optimization loop to improve manufacturing robot FDM print configuration selection. By treating the LLM as a tuning expert that suggests corrective actions based on structured diagnostic feedback, the method found it significantly outperformed default settings and end-to-end AI recommendations, achieving near-perfect configurations on 78% of objects.