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Reverse Engineering

Reverse Engineering. Dr. G ábor Renner Geometric Modelling Laboratory, Computer and Automation Research Institute. Reverse Engineering.

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Reverse Engineering

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  1. Reverse Engineering Dr. Gábor Renner Geometric Modelling Laboratory, Computer and Automation Research Institute Reverse Engineering

  2. Reverse Engineering • set data point  CAD model measured data  boundary representation (incomplete, noisy, outliers) (accurate and consistent) • intelligent 3D Scanner • interpret the structure of data points in order to create an appropriate computer representation allowing redesign of objects • applications • no original drawing or documentation • reengineering for constructing improved products • reconstruct wooden or clay models • incorporate, matching human surfaces, etc. Reverse Engineering

  3. Classifying objects • conventional engineering objects • many faces; mostly simple geometry • f(x,y,z)=0, implicit surfaces: • plane, cylinder, cone, sphere, torus • sharp (or blended) edges • free - form shapes • small number of faces; complex geometry • r = r(u,v), piecewise parametric surfaces, • smooth internal subdividing curves • artistic objects • natural surfaces Reverse Engineering

  4. Conventional engineering parts Reverse Engineering

  5. Free-form objects Reverse Engineering

  6. Artistic objects Reverse Engineering

  7. Natural object Reverse Engineering

  8. Natural objects Reverse Engineering

  9. Natural objects Reverse Engineering

  10. Basic Phases of RE • 1. data acquisition • 2. pre-processing • triangulation, • decimation • merging multiple views • 3. segmentation • 4. surface fitting • 5. CAD model creation Reverse Engineering

  11. Triangulation Reverse Engineering

  12. Triangulation Reverse Engineering

  13. Decimation Reverse Engineering

  14. Merging point clouds (registration) - 1 Reverse Engineering

  15. Merging point clouds (registration) - 2 FIAT Reverse Engineering

  16. Segmentation and surface fitting • SEGMENTATION: separate subsets of data points; each point region corresponds to the pre-image of a particular face of the object • “chicken and egg” problem • given the geometry, selecting point sets is easy • given the pointsets, fitting geometry is easy • to resolve this we need: • interactive help • iterative procedures • restricted object classes • segmentation and surface fitting are strongly coupled: hypothesis  tests Reverse Engineering

  17. Reconstructing conventional engineering objects - 1 • basic assumptions • relatively large primary surfaces • planes, cylinders, cones, spheres, tori • linear extrusions and surfaces of revolution • relatively small blends • “accurate” reconstruction”without” user assistance Reverse Engineering

  18. Object and decimated mesh Reverse Engineering

  19. Reconstructing conventional engineering objects - 2 • the basic structure can be determined • direct segmentation • decompose the point cloud into regions • a sequential approach using filters • find “stable” regions • discard “unstable” triangular strips, by detecting sharp edges and smooth edges • simple regions • composite, smooth regions Reverse Engineering

  20. Reconstructing conventional engineering objects - 3 • sharp edges (and edges with small blends) • computed by surface-surface intersection • smooth edges • assure accuracy and tangential continuity • surface/surface intersections would fail in the almost tangential situations • explicitly created by constrained fitting of multiple geometric entities Reverse Engineering

  21. Direct segmentation - 1 • basic principle • 1. based on a given environment compute an indicator for each point • 2. based on the current filter exclude unstable portions and split the region into smaller ones • 3. if simple region: done • 4. if linear extrusion or surface of revolution: create a 2D profile • 5. if smooth, composite region: compute the next indicator and go to 1 Reverse Engineering

  22. Direct segmentation - 2 • planarityfilter: detect sharp edges and small blends • dimensionalityfilter: separate • planes • cylinders or cones, linear extrusions, composite conical-cylindrical regions • spheres or tori, surfaces of revolution, composite toroidal-spherical regions • directionfilter: separate • cylinders, linear extrusions, composite conical regions • apex filter: separate cones • axis filter: separate • spheres, tori, surfaces of revolution Reverse Engineering

  23. Planarity filtering Remove data points around sharp edges Angular deviation Numerical curvatures Reverse Engineering

  24. Dimensionality filtering using the Gaussian sphere Reverse Engineering

  25. Dimensionality filtering - An example. Reverse Engineering

  26. Dimensionality filtering • separate data points by their dimensionality • based on the number of points in two concentric spheres D0: planes D1: cylinders-cones-transl. surfs D2: tori-spheres-rot. surfs Reverse Engineering

  27. Planarity and dimensionality filtering Reverse Engineering

  28. Planarity and dimensionality filtering Reverse Engineering

  29. Detect translational and rotational symmetries • translational direction • normal vectors ni of a translational surface are perpendicular to a common direction • minimise   ni,d2 • rotational axis • normal lines of a rotational surface (li, pi) intersect a common axis • i - angle between the normal line liand the plane containing the axis and the point pi • various measures, in general: a non-linear system Reverse Engineering

  30. Computing best fit rotational axis Reverse Engineering

  31. Conical - cylindrical region direction estimation detects cylinders and composite linear extrusions, rest: composite conical region Reverse Engineering

  32. Conical composite region fit a least squares point to the tangent planes to compute the apex Reverse Engineering

  33. Toroidal - spherical region estimate a local axis of revolution if largest eigenvalue (almost) zero -> sphere otherwise torus or surface of revolution Reverse Engineering

  34. Apex and axis filtering Reverse Engineering

  35. Surface fitting • given a point set and a hypothesis - find the best least squares surface • simple analytic surfaces - f(s,p) = 0 • s: parameter vector, p: 3D point • minimise Euclidean distances - true geometric fitting • algebraic fitting - minimise  f(s,pi )2 • approximate geometric fit - f / | f ’| • ‘faithful’ geometric distances (Pratt 1987, Lukács et al., 1998): unit derivative on the surface • sequential least squares • based on normal vector estimations • series of linear steps • reasonably accurate, computationally efficient Reverse Engineering

  36. Constrained fitting • needed for various engineering purposes • fitting smooth profile curves for linear extrusions and surfaces of revolution • refitting elements of smooth composite regions for B-rep model building • good initial surface parameters from segmentation • set of constraints • edge curves - explicitly computed • beautify the model • resolve topological inconsistencies • rounded values, perpendicular faces, concentric axis Reverse Engineering

  37. Constrained fitting Reverse Engineering

  38. Constrained profiles Translational profile Rotational profile Reverse Engineering

  39. Constrained fitting problem • primary surfaces: s  S • parameter set:a • point sets: p  Ps • individual weight: s • k constraint equations: {ci} • finda, which minimizes f while c=0 c(a) = 0 Constraints: tangency, perpendicularity, concentricity, symmetry, etc.. Reverse Engineering

  40. Constrained fitting techniques • standard solution: Lagrangian multipliers, n+k equations, multidimensional Newton-Raphson • problem: constraints contradict or not independent • preferred solution: sequential constraint satisfaction constraints sorted by priority • c(a) = 0 and f(a) = min. is solved simultaneously by iteration Reverse Engineering

  41. Constrained fitting - 2 • linear approximation for c, quadratic for f • in matrix form • where Reverse Engineering

  42. Efficient representation • signed distance function • the function to be minimized • middle term needs to be computed only once Reverse Engineering

  43. Fitting a circle - an example • center o, radius r, point p • Euclidean distance function: |p - o| - r • faithful approximation: • terms are now separated • alternative parameters with a constraint: Reverse Engineering

  44. Equations for constrained fitting of circles • circles (lines) - in Pratt’s form (1987) • tangency constraints Reverse Engineering

  45. Using auxiliary objects 1a 1b 2a 2b Reverse Engineering

  46. Simple part reconstruction Reverse Engineering

  47. Final CAD (B-rep) model  without blends with blends  Reverse Engineering

  48. Reconstruction of free-form shapes P3 P4 S2 P5 P2 P7 ST(S1,S2) P1 P6 P8 S1 Functional decomposition: primary surfaces + features Ignore area P0 P10 Reverse Engineering

  49. Reconstruction of free-form shapes Surface structure Reverse Engineering

  50. Reconstruction of free-form shapes Curvature plot Reverse Engineering

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