Mechanical geometry theorem proving
Mechanical geometry theorem proving
Variation of geometrics based on a geometric-reasoning method
Computer-Aided Design
Algebraic methods for geometric reasoning
Annual review of computer science: vol. 3, 1988
Algebraic solution for geometry from dimensional constraints
SMA '91 Proceedings of the first ACM symposium on Solid modeling foundations and CAD/CAM applications
A graph-constructive approach to solving systems of geometric constraints
ACM Transactions on Graphics (TOG)
Geometric Constraint Solving and Applications
Geometric Constraint Solving and Applications
Solving Geometric Constraints By Homotopy
IEEE Transactions on Visualization and Computer Graphics
A Hybrid Constraint Solver Using Exact and Iterative Geometric Constructions
CAD Systems Development: Tools and Methods [Dagstuhl Seminar, 1995]
Solving Geometric Constraints by a Graph-Constructive Approach
IV '99 Proceedings of the 1999 International Conference on Information Visualisation
Dealing with redundancy and inconsistency in constructive geometric constraint solving
Advances in Engineering Software
A 2D geometric constraint solver using a graph reduction method
Advances in Engineering Software
Proceedings of the 2011 ACM Symposium on Applied Computing
A particle-spring approach to geometric constraints solving
Proceedings of the 2011 ACM Symposium on Applied Computing
| Hi-index | 0.00 |
In this paper, a graph constructive approach to solving geometric constraint problems is being described. Usually, the graph constructive approach is efficient; however, it has its limitations in scope: it cannot handle ruler-and-compass non-constructible configurations, and under-constrained problems. To overcome these limitations, a proposed algorithm that isolates ruler-and-compass non-constructible configurations from ruler-and-compass constructible configurations is made. Numerical calculation methods are applied to solve them separately. This separation can maximize the efficiency and robustness of a geometric constraint solver. Moreover, the solver can handle under-constrained problems by classifying under-constrained subgraphs to simplified cases by applying classification rules. Then, it decides the calculating sequence of the geometric entities in each classified case, and calculates the geometric entities by adding appropriate assumptions or constraints. By extending the clustering types, and defining several rules, the proposed approach can overcome the limitations of previous graph constructive approaches. Therefore, an efficient and robust geometric constraint solver using this approach can be made.