New geometric constraint solving formulation: Application to the 3D pentahedron

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Abstract

Geometric Constraint Solving Problems (GCSP) are nowadays routinely investigated in geometric modeling. The 3D Pentahedron problem is a GCSP defined by the lengths of its edges and the planarity of its quadrilateral faces, yielding to an under-constrained system of twelve equations in eighteen unknowns. In this work, we focus on solving the 3D Pentahedron problem in a more robust and efficient way, through a new formulation that reduces the underlying algebraic formulation to a well-constrained system of three equations in three unknowns, and avoids at the same time the use of placement rules that resolve the under-constrained original formulation. We show that geometric constraints can be specified in many ways and that some formulations are much better than others, because they are much smaller and they avoid spurious degenerate solutions. Several experimentations showing a considerable performance enhancement (x42) are reported in this paper to consolidate our theoretical findings. © 2014 Springer International Publishing.

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APA

Barki, H., Cane, J. M., Michelucci, D., & Foufou, S. (2014). New geometric constraint solving formulation: Application to the 3D pentahedron. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8509 LNCS, pp. 594–601). Springer Verlag. https://doi.org/10.1007/978-3-319-07998-1_68

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