AutoForma: A Large Language Model-Based Multi-Agent for Computer-Automated Design
With the proliferation of artificial intelligence, Computer-Aided Design (CAD) is being transformed into Computer-Automated Design (CAutoD). In this paper, the advent of Large Language Models (LLMs) introduces new opportunities for CAutoD. This study develops AutoForma, an LLM-based multi-agent system, for automatic conversion from natural language descriptions to 3D models. By harnessing the comprehension capabilities of LLMs, AutoForma streamlines the CAutoD workflow by efficiently translating design intents into precise models in CAD. Through a comprehensive set of evaluations, AutoForma is seen to offer automation performance across various design tasks, particularly in generating non-standard parts that meet specific requirements, with higher efficiency and accuracy than using just an LLM like GPT-4.
Authors
- Shui Yu (ORCID: https://orcid.org/0000-0003-4485-6743)
- Yangmin Li (ORCID: https://orcid.org/0000-0002-4448-3310)
- Jixian Xu (ORCID: https://orcid.org/0000-0001-8119-3411)
- Ziche CHEN (ORCID: https://orcid.org/0009-0008-7095-7250)
- Jiahua Liao (ORCID: https://orcid.org/0000-0001-8576-8622)
- Sailing He (ORCID: https://orcid.org/0000-0002-3401-1125)
Publication Details
- Published
- 2024-10-06
- DOI
- https://doi.org/10.1109/smc54092.2024.10831565
- Citations
- 1
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- National Natural Science Foundation of China