关键词: 三维CAD建模, Transformer, 命令生成, 几何约束, 自动化设计, 高斯容错交叉熵

Abstract: In intelligent Computer-Aided Design (CAD), a key challenge is to enable three-dimensional model automatic generation systems to not only follow precise geometric constraints but also tolerate reasonable manufacturing errors. The traditional cross-entropy loss function, commonly used in generative models, tends to over-penalize minor parameter deviations. Additionally, it fails to adequately incorporate attribute constraints — such as area or volume — during the modeling process, often resulting in generated outputs that deviate from engineering realities.To address these issues, a CAD command generation method based on a Gaussian tolerant cross-entropy loss function — named GTCG-Transformer (Gaussian Tolerant CAD Generation Transformer) — was proposed. The core innovations of this method include: 1) A Gaussian fault-tolerant cross-entropy loss function was designed. By introducing Gaussian weights to smooth the target value neighborhood, the model is enabled to distinguish "serious errors" from "acceptable deviations," significantly improving fault tolerance for continuous parameter prediction. 2) A Transformer generation architecture with embedded geometric constraints was constructed. Geometric attributes such as area and volume were encoded as conditional inputs to drive the decoder to generate CAD command sequences complying with preset constraints, achieving constraint-aware end-to-end automated design. Experimental results on the filtered DeepCAD dataset indicate that GTCG-Transformer comprehensively outperforms mainstream baseline models in predicting geometric attributes like area and volume. Specifically, under dual constraints of area and volume, compared with the state-of-the-art CAD-LM (Computer-Aided Design-Language Model) method, the proposed method achieves the best performance in Mean Square Error (MSE), Mean Absolute Error (MAE), and Pearson Correlation Coefficient (PCC), with the area MSE reduced to 1.262 and the volume MSE reduced to 0.018.This research provides a novel method with controllable constraints and robust fault tolerance for CAD automatic generation, demonstrating clear application potential in fields requiring high-precision geometric compliance, such as intelligent manufacturing and parametric design.

Key words: Three-dimensional CAD modeling, Transformer, Command generation, Geometric constraints, Automated design, Gaussian fault-tolerant cross-entropy