DOI: 10.1049/dgt2.12014 ISSN: 2995-5629

CADGen: Computer‐aided design sequence construction with a guided codebook learning

Shengdi Zhou, Xiaoqiang Zan, Zhuqing Li, Bin Zhou

Abstract

Computer‐aided design (CAD) software continues to be a crucial tool in digital twin application and manufacturing, facilitating the design of various products. We present a novel CAD generation method, an agent that constructs the CAD sequences containing the sketch‐and‐extrude modelling operations efficiently and with high quality. Starting from the sketch and extrusion operation sequences, we utilise the transformer encoder to encode them into different disentangled codebooks to represent their distribution properties while considering their correlations. Then, a combination of auto‐regressive and non‐autoregressive samplers is trained to sample the code for CAD sequence construction. Extensive experiments demonstrate that our model generates diverse and high‐quality CAD models. We also show some cases of real digital twin applications and indicate that our generated model can be used as the data source for the digital twin platform, exhibiting designers' potential.

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