Papers by Artur A Gonçalves
Meshes are considered the gold standard regarding contact geometries of many mechanical models, e... more Meshes are considered the gold standard regarding contact geometries of many mechanical models, even those represented with discrete surface contact elements. However, meshes may not be the best formulations when controlled precision and execution time become paramount. In this paper, we address parametric and implicit formulations for precise contact distance estimations between superovoidal shapes, which generalize superellipsoids. Parametric and implicit models provide more compact descriptions than meshes, while making it possible to approximate mechanical parts with great precision. Contrary to meshes, these geometric representations can then support fast calculation of distances with arbitrary precision without paying a storage or computation time penalty. We performed a benchmark study to compare different superellipsoidal and superovoidal contact geometry representations, including implicit surfaces, parametric surfaces and triangular meshes. We tested 10,000 contact pairs and also considered two application cases: robot fingers of an iCub and dental occlusion during bite. Our results show that the implicit model is the most efficient contact geometry representation, followed by parametric and mesh surfaces. In addition, results show that either implicit or parametric superovoids can provide more accurate distance estimations than meshes in practical settings where precise contact points, surface normals and clearance estimations are required.
In this work, MacConaill’s classification that the articular surface
of the femoral head is bette... more In this work, MacConaill’s classification that the articular surface
of the femoral head is better represented by ovoidal shapes rather
than purely spherical shapes is computationally tested. To test
MacConaill’s classification, a surface fitting framework was
developed to fit spheres, ellipsoids, superellipsoids, ovoids, and
superovoids to computed tomography (CT) data of the femoral
proximal epiphysis. The framework includes several image processing
and computational geometry techniques, such as active
contour segmentation and mesh smoothing, where implicit surface
fitting is performed with genetic algorithms. By comparing
the surface fitting error statistics, the results indicate that
(super)ovoids fit femoral articular surfaces better than spherical
or (super)ellipsoidal shapes.
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Papers by Artur A Gonçalves
of the femoral head is better represented by ovoidal shapes rather
than purely spherical shapes is computationally tested. To test
MacConaill’s classification, a surface fitting framework was
developed to fit spheres, ellipsoids, superellipsoids, ovoids, and
superovoids to computed tomography (CT) data of the femoral
proximal epiphysis. The framework includes several image processing
and computational geometry techniques, such as active
contour segmentation and mesh smoothing, where implicit surface
fitting is performed with genetic algorithms. By comparing
the surface fitting error statistics, the results indicate that
(super)ovoids fit femoral articular surfaces better than spherical
or (super)ellipsoidal shapes.
of the femoral head is better represented by ovoidal shapes rather
than purely spherical shapes is computationally tested. To test
MacConaill’s classification, a surface fitting framework was
developed to fit spheres, ellipsoids, superellipsoids, ovoids, and
superovoids to computed tomography (CT) data of the femoral
proximal epiphysis. The framework includes several image processing
and computational geometry techniques, such as active
contour segmentation and mesh smoothing, where implicit surface
fitting is performed with genetic algorithms. By comparing
the surface fitting error statistics, the results indicate that
(super)ovoids fit femoral articular surfaces better than spherical
or (super)ellipsoidal shapes.