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Geometric constraint subsets and subgraphs in the analysis of assemblies and mechanisms

机译:装配和机构分析中的几何约束子集和子图

摘要

Geometric Reasoning ability is central to many applications in CAD/CAM/CAPP environments -- An increasing demand exists for Geometric Reasoning systems which evaluate the feasibility of virtual scenes specified by geometric relations -- Thus, the Geometric Constraint Satisfaction or Scene Feasibility (GCS/SF) problem consists of a basic scenario containing geometric entities, whose context is used to propose constraining relations among still undefined entities -- If the constraint specification is consistent, the answer of the problem is one of finitely or infinitely many solution scenarios satisfying the prescribed constraints -- Otherwise, a diagnostic of inconsistency is expected -- The three main approaches used for this problem are numerical, procedural or operational and mathematical -- Numerical and procedural approaches answer only part of the problem, and are not complete in the sense that a failure to provide an answer does not preclude the existence of one -- The mathematical approach previously presented by the authors describes the problem using a set of polynomial equations -- The common roots to this set of polynomials characterizes the solution space for such a problem -- That work presents the use of Groebner basis techniques for verifying the consistency of the constraints -- It also integrates subgroups of the Special Euclidean Group of Displacements SE(3) in the problem formulation to exploit the structure implied by geometric relations -- Although theoretically sound, these techniques require large amounts of computing resources -- This work proposes Divide-and-Conquer techniques applied to local GCS/SF subproblems to identify strongly constrained clusters of geometric entities -- The identification and preprocessing of these clusters generally reduces the effort required in solving the overall problem -- Cluster identification can be related to identifying short cycles in the Spatial Con straint graph for the GCS/SF problem -- Their preprocessing uses the aforementioned Algebraic Geometry and Group theoretical techniques on the local GCS/SF problems that correspond to these cycles -- Besides improving theefficiency of the solution approach, the Divide-and-Conquer techniques capture the physical essence of the problem -- This is illustrated by applying the discussed techniques to the analysis of the degrees of freedom of mechanisms
机译:几何推理能力对于CAD / CAM / CAPP环境中的许多应用至关重要-评估几何关系指定的虚拟场景的可行性的几何推理系统的需求日益增长-因此,几何约束满意度或场景可行性(GCS / SF)问题由一个包含几何实体的基本方案组成,该几何方案的上下文用于建议仍未定义的实体之间的约束关系-如果约束条件是一致的,则问题的答案是满足指定条件的有限或无限多个解决方案方案之一约束-否则,将需要对不一致进行诊断-用于此问题的三种主要方法是数值,过程或操作性和数学性-数值和过程性方法仅回答部分问题,并且在以下方面并不完整不提供答案并不排除一个答案的存在-数学作者先前提出的一种方法是使用一组多项式方程来描述这个问题-这组多项式的共同根刻画了这个问题的解空间-该工作提出了使用Groebner基技术来验证问题的一致性。约束条件-它还在问题公式中整合了特殊欧几里得位移SE(3)的子组以利用几何关系所隐含的结构-尽管从理论上讲是合理的,但是这些技术需要大量的计算资源-这项工作提出了适用于局部GCS / SF子问题的分治法技术,用于识别几何实体的强约束集群-这些集群的识别和预处理通常会减少解决整体问题所需的工作-集群识别可以与识别短时相关GCS / SF问题的空间约束图循环-预处理ing在与这些循环相对应的局部GCS / SF问题上使用了上述代数几何和群论技术-除提高求解方法的效率外,分治法还捕获了问题的物理本质–这是通过将讨论的技术应用于机构自由度的分析来说明

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