FR-CSG: Fast and Reliable Modeling for Constructive Solid Geometry.

Area of Science:

• Computer-Aided Design (CAD)
• Reverse Engineering
• Computational Geometry

Background:

• Challenges in Constructive Solid Geometry (CSG) reconstruction include capturing geometric details and efficiency.
• Existing methods suffer from topological errors and zero-volume surfaces due to discretization issues with non-axis-aligned primitives.

Purpose of the Study:

• To propose a novel workflow for fast CSG reconstruction and reliable forward modeling.
• To address limitations in geometric detail preservation and topological integrity in existing CSG reconstruction techniques.

Main Methods:

• Employs feature removal and model subdivision for efficient model decomposition.
• Introduces optimized primitive generation, filtering, and size-related reconstruction approaches.
• Develops a coplanar primitive discretization method and coplanar-aware Boolean tree assessment.

Main Results:

• Achieves fast CSG reconstruction and reliable forward modeling.
• Preserves intricate geometric details and ensures conciseness, semantic integrity, and editability of CSG trees.
• Generates manifold and watertight modeling results without zero-volume surfaces, even in degenerate cases.

Conclusions:

• The proposed method significantly outperforms state-of-the-art approaches in CSG reconstruction.
• Reconstructed CSG trees possess rich semantic information, facilitating diverse model editing tasks.
• Enables robust and accurate CSG modeling, overcoming limitations of previous methods.