Decomposing the problem of constrained surface fitting in reverse engineering
This paper presents a practical solution for surface fitting problems with prioritized geometry constraints in reverse engineering. The approach allows prioritizing constraints and uses them for decomposing the problem into a set of sequentially solved, manageable sub-problems. The result of each solution step is trade-off between satisfying the set of constraints and fitting of the surfaces to the measured points. The overall solution process trades off solution quality with complexity of the problem. Solution quality is checked against pre-defined tolerances assigned to the geometry constraints. Results on a benchmark problem demonstrate the suitability of the approach to solving large problems with hundreds of surfaces and constraints.
reverse engineering geometry constraints problem decomposition design structure matrix clustering partitioning