Decomposition plans for geometric constraint systems, part I: performance measures for CAD
Journal of Symbolic Computation
Decomposition plans for geometric constraint problems, part II: new algorithms
Journal of Symbolic Computation
Graph and combinatorial algorithms for geometric constraint solving
Graph and combinatorial algorithms for geometric constraint solving
Algorithms in Real Algebraic Geometry (Algorithms and Computation in Mathematics)
Algorithms in Real Algebraic Geometry (Algorithms and Computation in Mathematics)
Multivariate (geometric) constraints solving using subdivision based solvers
Proceedings of the 2007 ACM symposium on Solid and physical modeling
Solving Polynomial Equations: Foundations, Algorithms, and Applications
Solving Polynomial Equations: Foundations, Algorithms, and Applications
Body-and-cad geometric constraint systems
Computational Geometry: Theory and Applications
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Graphs of pairwise incidences between collections of rigid bodies occur in many practical applications and give rise to large algebraic systems for which all solutions have to be found. Such pairwise incidences have explicit, simple and rational parametrizations that, in principle, allow us to partially resolve these systems and arrive at a reduced, parametrized system in terms of the rational parameters. However, the choice of incidences and the partial order of incidence resolution strongly determine the algebraic complexity of the reduced, parametrized system-measured primarily in the number of variables and secondarily in the degree of the equations. Using a pairwise overlap graph, we introduce a combinatorial class of incidence tree parametrizations for a collection of rigid bodies. Minimizing the algebraic complexity over this class reduces this to a purely combinatorial optimization problem that is a special case of the set cover problem. We quantify the exact improvement of algebraic complexity obtained by optimization and illustrate the improvement by examples that cannot be solved without optimization. Since incidence trees represent only a subclass of possible parametrizations, we characterize when optimizing over this class is useful. That is, we show what properties of standard collections of rigid bodies are necessary for an optimal incidence tree to have minimal algebraic complexity. For a standard collection of rigid bodies, the optimal incidence tree parametrization offers lower algebraic complexity than any other known parametrization.