用圆锥曲线求解几何约束问题

几何约束求解广泛应用于机械设计,化学分子形成,几何定理证明和勘探等诸多领域,用于求解几何约束问题主要有3种方法：数值方法,符号方法和构造法,构造法用于具有简单易行的特点,因此被大多数的参数化机械设计系统作为求解几何约束问题的基本方法,针对构造法中只采用直线和圆,即直尺和圆规,来作为基本的作图工具,引进了一种新的作图工具,圆锥曲线,并且证明了在引进圆锥曲线以后,作图的范围明显大于只用直尺和圆规作图的范围;证明了一个图形能用圆锥曲线作出的充分必要条件是这个图形可以用一个三角化的次数小于等于4的方程组来描述;由于三次和四次方程的解可以显式地表示出来,所以引进圆锥曲线作为一个新的作图工具仍然可以保持原来尺规作图的简洁性和完整性。     

Geometric constraint solving with geometric transformation

This paper proposes two algorithms for solving geometric constraint systems. The first algorithm is for constrained systems without loops and has linear complexity. The second algorithm can solve constraint systems with loops. The latter algorithm is of quadratic complexity and is complete for constraint problems about simple polygons. The key to it is to combine the idea of graph based methods for geometric constraint solving and geometric transformations coming from rule-based methods.     

Solving spatial basic geometric constraint configurations with locus intersection

A basic idea of geometric constraint solving (GCS) is to decompose the constraint problem into smaller ones according to some basic configurations. In this paper, we find all spatial basic configurations involving points, lines, and planes containing up to six geometric primitives in an automated way. Many of these basic configurations still resist effective analytical solutions. We propose the locus intersection method (LIM) for GCS, a hybrid method based on geometric computation and numerical search that can be used to find all the solutions for a geometric constraint problem. We show that the LIM can be used to solve all the above basic configurations.     

用连杆机构几何约束求解

在这篇文章里,我们引入连杆机构作为新的工具,且证明这是完备的,也就是说,所有能构造性描述的图形能被连杆机构作出,这一类包括了所有只含距离约束的约束问题.作为一个应用,我们说明了超出Owen和Hoffmann的三角分解方法之外的最简单的约束图能被转化为纯几何构造形式.为了求解起源于连杆构造的方程,我们提出了一种基于动态轨迹生成的几何方法.     

A C-tree decomposition algorithm for 2D and 3D geometric constraint solving

In this paper, we propose a method which can be used to decompose a 2D or 3D constraint problem into a C-tree. With this decomposition, a geometric constraint problem can be reduced into basic merge patterns, which are the smallest problems we need to solve in order to solve the original problem in certain sense. Based on the C-tree decomposition algorithm, we implemented a software package MMP/Geometer. Experimental results show that MMP/Geometer finds the smallest decomposition for all the testing examples efficiently.     

Dealing with redundancy and inconsistency in constructive geometric constraint solving

General constructive geometric constraint solvers are pre-processed by a degree-of-freedom analysis, which enables efficient graph decomposition and recombination. However, all these methods are based on the assumption that structural rigidity automatically assures solvability. In this paper, we show that this assumption fails in numerous, even the most basic, configurations. We introduce several simple but efficient rules aimed to additionally analyse solvability in such cases. Another novelty addresses conditional constraints between three or more geometric parts, rules for their simplification and a redundancy check. All these functionalities are built into our original 2D geometric constraint solver, based on concepts of rigid clusters and constrained-angle (CA) sets.     

Geometric constraint solving: The witness configuration method

Geometric constraint solving is a key issue in CAD, CAM and PLM. The systems of geometric constraints are today studied and decomposed with graph-based methods, before their numerical resolution. However, graph-based methods can detect only the simplest (called structural) dependences between constraints; they cannot detect subtle dependences due to theorems. To overcome these limitations, this paper proposes a new method: the system is studied (with linear algebra tools) at a witness configuration, which is intuitively similar to the unknown one, and easy to compute.     

基于改进鱼群算法的几何约束求解

几何约束求解是CAD建模中的关键技术。针对求解质量不高和求解速度慢的问题,进行了研究。提出了一种鱼群算法和混沌算法相结合的几何约束求解方法。首先,将CAD模型中的几何约束关系表示为一组代数方程组;然后,利用代数方程组来构造目标函数。将几何约束求解问题转换为目标函数的优化问题。最后,使用混沌算法来改进鱼群算法以寻找目标函数的最优解。实验结果表明：该方法可以有效地解决几何约束问题。     

三维服装CAD中几何约束表达及其求解技术研究

从人体及服装的特点出发,提出三维服装几何元素的概念．采用样条曲线作为基本几何元素,归纳出服装的三种约束关系,即共点、对称和自对称关系;成为约束关系形成的基础．以三种约束关系为基础,建立了面向服装的几何约束图,有效地表达了三维服装几何元素及其相互关系;实现了一种基于约束图的约束求解方法。从而完成了构造服装及对服装的交互参数化修改,文中给出了应用实例,并将参数化方法向高层次图素如样条曲线、曲面作了推广,成功地应用于以样条曲线为几何元素的参数化服装CAD系统中,运行效果良好。     

A constructive approach to calculate parameter ranges for systems of geometric constraints

Geometric constraints are at the heart of parametric and feature-based CAD systems. Changing values of geometric constraint parameters is one of the most common operations in such systems. However, because allowable parameter values are not known to the user beforehand, this is often a trial-and-error process. We present an approach for automatically determining the allowable range for parameters of geometric constraints. Considered are systems of distance and angle constraints on points in 3D that can be decomposed into triangular and tetrahedral subproblems, by which most practical situations in parametric and feature-based CAD systems can be represented. Our method uses the decomposition to find critical parameter values for which subproblems degenerate. By solving one problem instance for each interval between two subsequent critical values, the exact parameter range is determined for which a solution exists.