CAD S YSTEMS AND A PPLICATIONS Ioannis Fudos a and Vasiliki Stamati b
4. CAD Applications from a Feature-Based/Constraint-Based Point of View
4.2. Feature-Based Modeling for Reverse Engineering
Reverse engineering aims to analyze a real object and to determine its characteristics and mechanisms, with further aim to reconstruct and remanufacture it. The data concerning the physical object can be obtained by various methods. A common method is using a 3D laser scanner to obtain a point cloud corresponding to points on the surface of the scanned object. Given this, a more specific definition of reverse engineering would be to define it as the process of obtaining a geometric CAD model from measurements acquired by scanning an existing physical model [65].
Reverse engineering is vital for various industries because the computer models acquired help improve the quality and efficiency of designs and also speed up the manufacturing and analysis process. In mechanical part engineering and manufacturing, reverse engineering aims to replicate existing parts for which no CAD models exist. Also, it is possible to manufacture objects for which the original CAD model no longer corresponds to the physical part that was manufactured due to subsequent undocumented modifications made after the initial design stage. Reverse engineering is applied in industrial design, such as automobile exterior parts design. Stylists and artists very often create physical models of their concepts by using clay, plaster or wood. These real-scale models are then used to create CAD models for manufacturing the objects on an industrial scale. Also the CAD models provide the artists and stylists with the ability to re-evaluate their designs, especially when they can easily re-design or modify them as needed. Reverse engineering encourages conceptual design because the designer creates an initial prototype, scans it and manipulates it as desired.
Re-engineering objects of freeform design is relatively more difficult and complex than reconstructing mechanical parts. Mechanical parts usually have specific geometric characteristics, such as symmetries and swept profiles that are fairly easy to detect and parameterize. However, in the case of freeform objects, there are often features that are difficult to extract. In the case of restricted mechanical parts, features libraries can be defined
and used for detecting features in the point cloud, whereas for freeform objects this is not feasible.
Since reverse engineering applications aim at reproduction and manufacturing, the re- engineering process must create highly accurate and robust CAD models. A characteristic of the objects re-engineered is that they are usually parts of larger objects and therefore have to fit and connect exactly with other parts, like pieces in a puzzle. For this reason, the models created through the reverse engineering process must be well defined and constrained [66]. Also, in some cases, the model created is to be edited in i.e. custom designing, therefore a simple B-rep model is not appropriate. Given this, it is natural that feature-based and constrained based models are used more and more in re-engineering applications.
A feature-based reverse engineering method was also used in [67] for reverse engineering a mannequin for garment design. The basic concept in this method is to create a generic mannequin model of a human torso, which is appropriately aligned with the 3D point cloud of the desired human torso model, and the generic model is “fitted” to the point cloud by matching up characteristic points of the models e.g. peaks. This method creates parameterized models by exploiting the features of the object and by using them to constrain the fitting process. It is an automated approach to reverse engineering human torsos that creates parameterized models with good accuracy.
Constraint definition and application has been used in building reconstruction and reverse engineering objects of aesthetic design. Specifically, [68] examines how a priori knowledge can be used to derive constraints to create more accurate models in architectural applications. Relevant work is also found in [69]. In [70] the authors suggest a constraint-based approach in reverse engineering for model beautification.
Figure 4. A point cloud of a screwdriver [74] (left) and its concavity intensity map (right).
A paradigm of feature-based/constraint-based re-engineering is the REFAB ([71], [48]) project, which uses a feature-based and constraint-based method to reverse engineer mechanical parts. REFAB is a human interactive system where the 3D point cloud is presented to the user, and the user selects from a list a feature that exists in the cloud, specifies with the mouse the approximate location of the feature in the point cloud, and the system then fits the specified feature to the actual point cloud data using a least square means method iteratively. The authors give emphasis on the fitting of pockets, where the user draws a profile of the pocket on the point cloud and the system then fits the profile to the data and the profile is then extruded to create the pocket. This feature-fitting process is made more
accurate by using constraints that are detected by the system, verified by the user and then exploited to achieve a better fitting of the features according to the data. The system supports constraints [72] such as parallelism, concentricity, perpendicularity and symmetry. The constraints defined and used in REFAB seek to reduce the degrees of freedom associated with the object as much as possible, so as to achieve high precision models in less time.
An interesting feature-based approach to re-engineering objects of freeform design is presented in [73]. Re-engineering objects of freeform design is essential for supporting custom design in a CAD model reconstruction system. It provides user-designers with the capability to modify re-engineered CAD models according to their preferences and to incorporate in novel designs. For instance, in the case of jewellery re-engineering, the user- designer might like to be able to modify the dimensions of a ring to produce one of larger size, or be able to choose certain parts of the object to use them to create other pieces of jewellery. To this end, one needs to exploit the features of the original model and the relationships and constraints that hold among them. In [73] a generic and global feature detection approach to reverse engineering point clouds of objects of freeform design is presented. A method is presented for detecting and segmenting a point cloud into individual subsets that correspond to features. This is achieved by using a point characteristic defined as “concavity intensity” to decompose the point cloud into subsets (components) that correspond to features of the physical object. The concavity intensity of a point corresponds to the smallest distance from the point to its convex hull that does not pass through the point cloud. This feature basically detects concave features in the object being reengineered. A concavity intensity map is shown in figure 4. In the concavity intensity map the values are rendered using greyscale, where black corresponds to points belonging to the convex hull, whereas white corresponds to points that are farthest away from the convex hull. We can observe that edges (rapid variations in concavity intensity), saddle points and extrema can be used to partition the point cloud into components that can later be refined as the features of the object.
Figure 5. Feature extraction is performed by region growing.
The point concavity intensity values calculated are used to segment the point cloud into feature components. A feature component is bounded by areas where abrupt changes in the direction of the normal and/or rapid concavity intensity variations are observed. After calculating the concavity intensities of the all the points that form the point cloud, a region
growing method to divide the point cloud into its components is applied (figure 5). The region growing method is based on two criteria:
i) the normal vectors of neighboring points belonging to the same region should form an angle smaller than a threshold t and
ii) the approximate gradients of the concavity intensity function in directions x, y and z for neighboring points of the same region should maintain the same sign value, meaning that there are no zero crossings observed between them.
5. Conclusion
We presented a survey of representation schemes for CAD applications. Then we introduced a framework for representing and performing complex design operations in CAD systems. This framework has evolved from the feature-based design paradigm augmented with arbitrary intra-feature and inter-feature constraints and a hierarchical constraint analysis approach for placing geometric elements. To demonstrate the employment of this framework we presented two example applications that we have developed using this new design concept.
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Chapter 8