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This study presents a method for enhancing robot body design efficiency through the integration of multi-objective black-box optimization and large language models (LLMs). By combining the strengths of LLMs for broad design exploration with the precision of black-box optimization, the proposed approach aims to minimize position error and required torque in robotic designs. Experimental results demonstrate that this method allows for more efficient exploration of design solutions compared to traditional blac

Author

Ace

Language

EN