Procedural CAD Model Reconstruction via Adaptive Sampling
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Solution Overview
Problem
Procedurally defined geometric models cannot be directly transferred between systems due to the need for human intervention in sampling points, leading to over-sampling and resulting in large data transfers and varying curve and surface models across different systems.
Innovation Solution
A computer-implemented method and apparatus that uses a callback function and required accuracy to sample procedurally defined geometry, constructing candidate curves and surfaces that meet specified accuracy, thereby reducing data transfer and ensuring consistency across systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human users manually determine and transfer sample points to achieve accurate reconstruction, then measurement precision is improved, but device complexity and loss of time increase
Solution Approach 1:
The system automatically determines the number and location of sample points through an adaptive sampling algorithm that evaluates the curvature and complexity of the procedurally defined geometry. The algorithm self-adjusts sampling density without human intervention, with higher density in high-curvature regions and lower density in flat regions, thereby achieving accurate reconstruction while eliminating manual complexity
Solution Approach 2:
The system dynamically changes sampling parameters (number of points, distribution density) based on geometric properties of the curve or surface being reconstructed. The adaptive algorithm modifies sampling density as a function of local curvature and feature importance, optimizing both accuracy and data efficiency
2Measurement precision
If over-sampling is used to achieve accuracy in reconstructed curves and surfaces, then measurement precision is improved, but quantity of substance increases due to large data transfers
Solution Approach 1:
The adaptive sampling algorithm applies different sampling densities to different regions of the geometry based on local characteristics. High-curvature regions and areas with significant geometric features receive higher sampling density, while flat or simple regions receive lower density. This local differentiation maintains reconstruction accuracy where needed while minimizing unnecessary data transfer in simple regions
Solution Approach 2:
Instead of uniformly over-sampling the entire geometry, the system applies sampling selectively based on geometric complexity. The algorithm determines the minimum necessary sampling density for each region to achieve the required accuracy threshold, avoiding excessive sampling in regions where it would not contribute to accuracy
3Adaptability or versatility
If different target systems use their own curve and surface fit methods to reconstruct from sample points, then adaptability is improved, but manufacturing precision deteriorates due to varying models across systems
Solution Approach 1:
The system performs preliminary adaptive sampling to generate an optimized set of sample points that capture the essential geometric features before transfer to the target system. By pre-processing the geometry to identify and sample critical features, the system ensures that the target system can reconstruct an accurate model even using its own fitting algorithms, thereby maintaining consistency across different systems
Solution Approach 2:
The adaptive sampling algorithm incorporates feedback loops that evaluate the quality of the sampled data and adjust sampling density accordingly. The system monitors geometric features and modifies sampling strategy to ensure that the transferred sample points contain sufficient information for accurate reconstruction, compensating for variations in target system reconstruction capabilities
Data Source
AI summary
The advantageous embodiments provide a computer implemented method, apparatus, and computer program product for constructing a computer aided design model. User input is received that contains a callback function and a required accuracy. The callback function prescribes a procedurally defined geometry and the required accuracy specifies the degree of accuracy needed for the computer aided design model. The callback function is sampled at a number of points to form sampled points and a candidate curve is constructed that approaches the sampled points. A determination is made as to whether the candidate curve meets the required accuracy.