A Constraint Programming Approach for Solving Rigid Geometric Systems

This paper introduces a new rigidification method -using interval constraint programming techniques- to solve geometric constraint systems. Standard rigidification techniques are graph-constructive methods exploiting the degrees of freedom of geometric objects. They work in two steps: a planning phase which identifies rigid clusters, and a solving phase which computes the coordinates of the geometric objects in every cluster. We propose here a new heuristic for the planning algorithm that yields in general small systems of equations. We also show that interval constraint techniques can be used not only to efficiently implement the solving phase, but also generalize former ad-hoc solving techniques. First experimental results show that this approach is more efficient than systems based on equational decomposition techniques.