The aim is to decide if a further constraint is consistent with the existing set of constraints imposed so far, and if it is, to satisfy it geometrically. We use an iterative optimisation process. Use geometric information from accepted constraints to derive iterative values of face normals. . Terminate when . No guarantee that optimisation is moving towards the answer .
Bad constraints slow the system down - they always take the maximum number of iterations .
Express face normals in terms of n independent variables. . Use a black-box optimisation routine to find the set of variables which minimises the objective function. . We might be trapped in a local minimum. . This method inherently slow as it makes no use of the geometric knowledge we already have . Bad constraints slow the system down - they always take the maximum number of iterations .