装配序列规划问题的CSP模型及其符号OBDD求解技术

完全、正确的可行装配序列的表示和生成是装配序列评价、优化和选择的前提,为此建立了单调非线性装配意义下的可行装配序列规划问题的约束满足问题(CSP)模型,并给出了基于有序二叉决策图(OBDD)的符号求解算法.首先以装配联接图和移动向量函数为装配体模型,给出了装配联接图模型的共享二叉决策图(SBDD)表示、移动向量函数的OBDD表示,以及装配序列规划问题的CSP描述;然后将生成所有可行装配序列的问题转化为对CSP求解所有可能解的问题,利用回溯算法对CSP问题进行符号OBDD求解,得到了满足几何可行性约束的所有可行装配序列.最后通过装配体实验验证了基于CSP模型和OBDD推理的装配序列生成技术的正确性和可行性.     

一类闭环约束的装配约束问题求解

分析了一种可以拆分为等价的开环约束的装配闭环约束问题.给出了等价性的定义,并提出一种该类闭环约束拆分为等价开环约束的方法.首先确定装配几何约束图上的闭环,然后对该闭环利用自由度归约加扰动判定是否从某一条边拆开.该方法能够较好的简化CAD软件中用户添加的装配约束,避免了因闭环约束造成的求解复杂度增加的情况,同时可以更好的表达实际装配的过程.     

基于规则和爆炸图的装配序列规划

提出局部爆炸图的概念，运用几何干涉规则生成各直角坐标方向的局部爆炸图；在确立各方向的合并顺序后，用合并规则生成各零件的合并约束前元集；并据此进行局部爆炸图合并求解装配序列，实现了规则推理和几何推理算法的紧密结合，有效地避免了装配序列组合爆炸，降低了装配规划的计算复杂度，保证规划所得装配序列的可行性和实用性．     

面向虚拟环境的装配体模型研究

人机交互是虚拟装配的本质特性和技术瓶颈，能反映交互过程的装配体模型构造，是虚拟装配领域的一个关键问题，给出一种时序的装配体模型，对时序的聚合关系、时序的约束关系以及时序的行为结构给出定义和分析，为实现该模型，还给出了零件的中间模型和对象复杂行为构造，同时对虚拟装配直接操作的交互过程、交互模式及装配工艺知识给出了时序的形式描述，这是连接人机交互与装配体模型以及模型与工艺生成的桥梁．一致的表示模型减少了交互装配信息的冗余性，有利于提高交互信息的复用，为交互生成工艺提出了新方法。     

基于装配约束动态管理的虚拟拆卸

装配约束是虚拟拆卸环境下必须考虑的装配体的重要信息，提出虚拟拆卸过程中装配约束的动态管理机制，并实现了基于装配约束导航的虚拟拆卸。装配约束的动态管理包括虚拟环境下装配约束的获取、表达以及拆卸过程中装配约束的动态维护，即装配约束的动态解除和产生，文中用装配约束图表达零件间的装配约束，提出装配约束的间接解除方法，并实现了基于装配约束推理的零件可拆卸方向的推导。最后，通过一个简单装配体的拆卸实例，对文中方法进行了验证。     

虚拟环境中面向装配设计的数据场景图研究

作为虚拟环境中的数据结构，场景图的构建是虚拟现实技术领域的重要研究问题之一。针对虚拟装配设计系统的要求，讨论现有商业VR软件在开发虚拟装配设计时存在的限制，提出一个基于场景图的多层次虚拟装配设计模型VAM．在现有VR软件和VAM的基础上，说明了虚拟装配设计时的路径规划、序列生成、零件之间的约束关系等的表示和应用。     

机器人化装配过程中的规则与判断支持

装配作业是一种精细复杂的智能控制作业.机器人化装配需要知识与判断的支持.本文阐述了装配作业的目标、主要装配关系和装配动作.给出了一组有关零部件拆卸装配的基本规则.探讨了约束的一种表征和移动拆卸的判断算法,在二维平面内验证了判断算法的可行性,给出了判断框图及源程序.     

特征向量变换求解装配约束的表示方法

基于装配零件的匹配特征的解析求解方法,利用装配特征的特征向量之间转换来确定零件之间的装配方向和相互位置关系．分析了平面之间共面、角度和平行约束,圆柱面之间同轴约束和圆锥面之间的重合等约束关系;并对几种常用的装配约束关系进行归类,给出了求解旋转矩阵和平移矩阵的统一的求解方法．文中方法同样适用于装配特征与装配体全局坐标轴倾斜情况．应用实例验证了该方法的有效性．     

基于图论的飞机典型装配工艺数据挖掘方法

为实现飞机装配指令编制的快速化、智能化,提出基于图论的飞机典型装配工艺数据挖掘方法。该方法将停用词表和分隔数组两个约束引入语义分词法完成装配工艺指令的分词处理,并以装配工艺特征向量结构化地表达分词后的装配工艺指令。将装配工艺特征向量映射为单向有序链,以此构建装配工艺图。通过定义装配工艺图的节点支持度和边支持度,给出了典型装配工艺挖掘方法。以某型飞机的平尾装配工艺为例,在多个支持度下验证了方法的有效性。     

基于约束的装配体技术

本文首先给出了装配体的数学模型与表示模型。系统采用二叉树来表示一个装配体，接着提出了基于约束表示的装配体位置关系的描述方法，约束通过转化以方程的形式求解，并对Ｎｅｗｔｏｎ迭代法提出了改进算法。     

Survey on assembly sequencing: a combinatorial and geometrical perspective

A systematic overview on the subject of assembly sequencing is presented. Sequencing lies at the core of assembly planning, and variants include finding a feasible sequence—respecting the precedence constraints between the assembly operations—, or determining an optimal one according to one or several operational criteria. The different ways of representing the space of feasible assembly sequences are described, as well as the search and optimization algorithms that can be used. Geometry plays a fundamental role in devising the precedence constraints between assembly operations, and this is the subject of the second part of the survey, which treats also motion in contact in the context of the actual performance of assembly operations.     

Forward Assembly Planning Based on Stability

The paper presents an approach to sequence planning consisting in determining assembly sequences defined in terms of mating and non-mating operations and based on a dynamic expansion of the assembly tree obtained using a knowledge base management system. The planner considers the case of a single-robot assembly workcell. The use of stability and the detailed definition of sequences also by means of several non-mating operations are shown to be powerful instruments in the control of the tree expansion. Forward assembly planning has been chosen, in order to minimize the number of stability checks. Backtracking is avoided by combining precedence relations and stability analysis. Hard and soft constrains are introduced to drive the tree expansion. Hard constraints are precedence relations and stability analysis. All operations are associated to costs, which are used as soft constraints. The operation based approach enables one to manage even non-mating operations and to easily overcome the linearity constraint. Costs enable the planner to manage the association among tools and components. The first section of the paper concerns Stability Analysis that is subdivided into Static and Dynamic Stability Analysis. The former is mainly involved in analyzing gravity effects; the latter is mainly involved in evaluate inertia effects due to manipulation. Stability Analysis is implemented in a simplified form. Fundamental assumptions are: no rotational equilibrium condition is considered; for each reaction force only direction and versus, but not magnitude, are considered; friction is neglected. The second section discusses the structure of the planner and its implementation. The planner is a rule based system. Forward chaining and hypothetical reasoning are the inference strategies used. The knowledge base and the data base of the system are presented and the advantages obtained using a rule based system are discussed. The third section shows two planning examples, showing the performance of the system in a simple case and in an industrial test case, the assembly of a microwave branching filter composed of 26 components.     

Design of a real-time AND/OR assembly scheduler on an optimization neural network

The problem of finding an AND/OR precedence-constraint assembly schedule using optimization neural computation is presented. The precedence relationships of assembly operation result from the geometric constraints of subtasks. Because of the existence of geometric constraints among assembly subtasks, the assembly operation involves AND/OR precedence relationships; that is, the order of assembly crucially determines whether the desired task can be achieved. A feasible assembly schedule is a schedule that satisfies these AND/OR precedence constraints.It has been shown that all the feasible assembly schedules can be generated by transforming geometric constraints of subtasks to the pattern-matching operation. Using the question-answer pattern and pattern-matching operation, the assembly scheduling problem can be transformed into an AND/OR precedence-constrained traveling salesman problem (TSP). Two precedence-constrained TSPs, cost-constrained TSP (CCTSP) and state-constrained TSP (SCTSP), are discussed. The CCTSP artificially sets the cost of the prohibited moves to a very large value which ensures that the constraints are satisfied, while the SCTSP restricts the movement of next assembly subtasks. The advantage of the SCTSP over CCTSP in the generation of the assembly schedule will be illustrated.A novel method proposed here is to obtain the best AND/OR precedence-constraint assembly schedule using neural network computation. The geometric constraints of an assembled object are transformed into the elements of the connection matrix which specifies the connection strength among neurons. A modified Hopfield network is used to tackle the AND/OR precedence-constraints assembly scheduling problem. Multirobot assembly sequences generation is also discussed. The designed algorithm can accommodate various constraints and applications. Detailed algorithms, examples and experiments are presented.     

改进遗传算法在装配操作优化中的应用

针对复杂车身连接关系和多装配顺序,改进后的装配模型不仅描述了零件间的装配优先关系,而且还包含了可以用于公差分析的装配连接特征信息.在此基础上,根据迂回遗传算法对零件间的装配操作进行优化,以提高优化效率及求解范围.最后,通过某车身侧围装配案例说明了该算法的有效性.     

Knowledge-based process planning for electronic assembly

The conventional method of electronic assembly planning is subjective and depends greatly on the skills, memory, knowledge and experience of the planners. This gives rise to inconsistencies which in turn create problems in the manufacturing environment. Since the computer logics are systematic and consistent, it is conceivable that an automatic electronic assembly planning system would have advances over manual systems. Due to the frequent advances in technology the electronic industry is a very dynamic one. This affects the effectiveness of the current process plans and the applicability of the system that generates them. In this paper important issues which address the automatic generation of process plans will be presented. The framework of a system which takes into account the dynamic nature of the environment will be introduced as an example.The original version of this paper was presented at the 2nd International Symposium on Robotics and Manufacturing (ISRAM), Albuquerque, New Mexico, 16–18 November 1988. The published proceedings of this meeting may be ordered from: CAD Laboratory for Systems/Robotics, EECE Dept., UNM, Albuquerque, NM 87131, U.S.A.     

一种基于配合约束的装配顺序产生算法

结合配合约束在装配中的应用,在分析装配零件的配合约束及其特点的基础上,得到零件之间的空间位置关系和零件的局部自由度,充分利用这些信息,引入优先装配方向和局部自由度表的概念,提出了一种基于最少装配方向的装配顺序自动生成算法。     

An interactive approach of assembly planning

An interactive approach to assembly planning is presented. It provides a virtual reality interface for production engineers to program the virtual representation of robotic manipulators in a three-dimensional (3D) operation space. The direct human involvement creates a user-defined assembly sequence, which contains the human knowledge of mechanical assembly. By extracting the precedence relationship of machinery parts, for the first time it becomes possible to generate alternative assembly sequences automatically from a single sequence for robot reprogramming. This interactive approach introduces human expertise into assembly planning, thus breaking down the computational complexity of autonomous systems. Experiments and analysis provide strong evidence to support the incontestable advantages of "manufacturing in the computer".     

An New Approach to Represent Assembly Sequences

How to identify all feasible assembly sequences and compactly represent them is very important and necessary to computer-aided assembly sequence planning. An approach to get precedence relationships between components directly from assembly modeling is proposed in this paper. A representation method called disassembly sequence graph (DSG) is also presented in this paper. An example has been provided to illustrate the proposed approach.     

Improving assembly precedence constraint generation by utilizing motion planning and part interaction clusters

In this paper, we present a technique that combines motion planning and part interaction clusters to improve generation of assembly precedence constraints. In particular, this technique automatically finds, and clusters, parts that can mutually affect each other’s accessibility, and hence may impose assembly constraints. This enables the generation of accurate precedence constraints without needing to examine all possible assembly sequences. Given an assembly model, our technique generates potential disassembly layers: spatial clustering is used to generate part sets. Next, motion planning based on rapidly-exploring random trees (RRT) with multiple trees is used to evaluate the interaction between these part sets. Specifically, motion planning is used to determine which part sets can be removed from the assembly. These sets are added to the first disassembly layer and removed from the assembly. Part sets that can be removed from the simplified assembly are then added to the second layer. If the process gets stuck, parts in the parent set are regrouped, and the process continues until all disassembly layers are found. The resulting structure reveals precedence relationships among part sets, which can be used to generate feasible assembly sequences for each part set and the whole assembly. We present theoretical results related to the algorithms developed in the paper. Computational results from tests on a variety of assemblies are presented to illustrate our approach.