🤖 AI Summary
Existing CAD systems suffer from a fundamental disconnect between feature-based parametric modeling and B-rep–based direct modeling, hindering cross-paradigm collaborative editing of geometry, topology, and parametric constraints. To address this, we propose a unified constraint graph model and a hybrid modeling kernel interface—enabling, for the first time, bidirectional, seamless integration of both paradigms. Our approach extends the constraint solver, introduces a topology-event–driven mapping mechanism, and designs parameter semantic extraction and incremental synchronization algorithms to support real-time, cross-mode collaboration. Evaluated on mainstream CAD platforms, our system achieves sub-80-ms editing latency, 99.2% constraint fidelity, and efficient handling of complex assemblies. This work breaks down longstanding paradigm barriers in CAD modeling and establishes a foundational architectural framework for next-generation intelligent CAD systems.
