Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation
Yichen Shi, Yuzhi Liu, Zhuofu Tao, Li Huang, Yuhao Gao, Ting-Jung Lin, Lei Hel
Abstract
A rich and recognizable component library is the cornerstone of printed circuit board (PCB) design and generation. Traditionally, engineers manually create symbols and footprints and design PCB schematics, which is time-consuming and error-prone. Leveraging multimodal large language models (MLLMs), we develop SFgen, an agentic recognition and generation flow of symbol and footprint for electronic components. SFgen achieves 86% accuracy for symbol generation and 80% accuracy for footprint generation. We use the SFgen method to create SFnet, a database of symbols and footprints. It now has 1000 components and is expanding constantly, which lays the foundation for automatic generation of PCB designs.
Topics
Classified with taxonomy v2 on Wed, 2 Sept 2026.