Heterogeneous fuzzy and game-based double-layer adaptive evolution CAD modeling command generation method

By constructing a closed-loop architecture for the entire process, the problems of fuzzy semantics and geometric parameter mapping, heterogeneous structure adaptation and game optimization in natural language-driven CAD command generation are solved, realizing high-fidelity, interpretable and executable CAD command generation, which is suitable for industrial design.

CN121809290AActive Publication Date: 2026-04-07UNIV OF ELECTRONICS SCI & TECH OF CHINA
2 Cites 1 Cited by

Patent Information

Application Number
CN202610274903.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-09
Publication Date
2026-04-07
Estimated Expiration
2046-03-09

AI Technical Summary

Technical Problem

Existing technologies cannot effectively solve the problems of accurate mapping between fuzzy semantics and geometric parameters, dynamic adaptation of heterogeneous structures, interpretability of generation logic, and multi-objective collaborative optimization in natural language-driven CAD command generation. This results in generated commands that are semantically fluent but not feasible in engineering and cannot meet the executability and auditing requirements of industrial design.

Method used

A two-layer adaptive evolutionary technology solution based on heterogeneous fuzzy logic and game theory is constructed. Through a closed-loop architecture of semantic parsing, encoding disambiguation, game generation, fuzzy evolution refinement, verification backtracking, and knowledge accumulation, a high-fidelity conversion from natural language to CAD commands is achieved. This includes fuzzy semantic quantization, dynamic adaptation of heterogeneous operators, dual-agent collaborative game optimization, and incremental learning.

Benefits of technology

It achieves a precise mapping from fuzzy semantics to accurate geometric parameters, adapts to CAD command structures of varying complexity, dynamically balances the interpretability, diversity, and executability of the generation logic, meets the auditing requirements of industrial design, and reduces the cost of model iteration development.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses a heterogeneous fuzzy and game-based double-layer adaptive evolution CAD modeling command generation method, and belongs to the technical field of artificial intelligence and computer-aided design intelligent modeling. The method solves the technical problems that in an existing natural language driven CAD command generation technology, fuzzy semantics are difficult to quantify and map, heterogeneous commands are poor in adaptability, the executable performance of generated commands is low, and the reasoning process is black-box-shaped. According to the method, a semantic analysis-game generation-evolution refinement-verification backtracking-knowledge precipitation full-process closed-loop architecture is constructed, the method can be applied to the fields of industrial software, three-dimensional modeling, intelligent design systems and the like, the engineering performability, generalization ability and reasoning interpretability of command generation are improved, the generation diversity and feasibility are balanced, and the method is suitable for popularization and application. And the model iteration cost is reduced, and technical support is provided for industrial landing of the text-driven CAD modeling technology.
Need to check novelty before this filing date? Find Prior Art