Construction of Robot Structure Design Support System by Constraint Logic Programming

Constraint Logic Programming (CLP) languages extend logic programming by allowing the use of constraints from different domains such as real numbers or Boolean functions. They have proved to be ideal for expressing problems that require interactive mathematical modeling and complex combinatorial optimization problems. However, CLP languages have mainly been considered as research systems, useful for rapid prototyping, by not really competitive with more conventional programming languages where efficiency is a more important consideration. One promising approach to improving the performance of CLP systems is the use of powerful program optimizations to reduce the cost of constraint solving. We extend work in this area by describing a new optimizing compiler for the CLP language CLP(ℛ). The compiler implements six powerful optimizations: reordering of constraints, removal of redundant variables, and specialization of constraints which cannot fail. Each program optimization is designed to remove the overhead of constraint solving when possible and keep the number of constraints in the store as small as possible. We systematically evaluate the effectiveness of each optimization in isolation and in combination. Our empirical evaluation of the compiler verifies that optimizing compilation can be made efficient enough to allow compilation of real-world programs and that it is worth performing such compilation because it gives significant time and space performance improvements.

The incorporation of global program analysis into recent compilers for Constraint Logic Programming (CLP) languages has greatly improved the efficiency of compiled programs. We present a global analyser based on abstract interpretation. Unlike traditional optimizers, whose designs tend to be ad hoc, the analyser has been designed with flexibility in mind. The analyser is incremental, allowing substantial program transformations by a compiler without requiring redundant re-computation of analysis data. The analyser is also generic in that it can perform a large number of different program analyses. Furthermore, the analyser has an object-oriented design, enabling it to be adapted to different applications easily and allowing it to be used with various CLP languages with simple modifications. As an example of this generality, we sketch the use of the analyser in two different applications involving two distinct CLP languages: an optimizing compiler for CLP(R) programs and an application for detecting occur-check problems in Prolog programs. © 1998 John Wiley & Sons Ltd.

In recent years, several constraintdbased temporal reasoning frameworks have been proposed. They consider temporal points or intervals as domain elements linked by temporal constraints. Temporal reasoning in these systems is based on constraint propagation. In this paper, we argue that a language based on constraint propagation can be a suitable tool for expressing and reasoning about temporal problems. We concentrate on Constraint Logic Programming (CLP) which is a powerful programming paradigm combining the advantages of Logic Programming and the efficiency of constraint solving. However, CLP presents some limitations in dealing with temporal reasoning. First, it uses an “arc consistency” propagation algorithm which is embedded in the inference engine, cannot be changed by the user, and is too weak in many temporal frameworks. Second, CLP is not able to deal with qualitative temporal constraints. We present a general meta CLP architecture which maintains the advantages of CLP, but overcomes these two main limitations. Each architectural level is a finite domain constraint solver (CLP(FD)) that reasons about constraints of the underlying level. Based on this conceptual architecture, we extend the CLP(FD) language and we specialize the extension proposed on Vilain and Kautz’s Point Algebra, on Allen’s Interval Algebra and on the STP framework by Dechter, Meiri and Pearl. In particular, we show that we can cope effectively with disjunctive constraints even in an intervaldbased framework.

A general constraint-based formulation for the analysis and partial synthesis of two-dimensional truss structures is presented. This formulation is general in that it handles statically determinate and statically indeterminate trusses with pin and roller supports, and concentrated joint loads. The formulation is constraint-based in that the physical behavior of truss components is declaratively represented using constraints.The analysis and partial synthesis of a truss structure manifest themselves in proving the satisfiability of the constraints associated with the structural components. An artificial intelligence approach called constraint logic programming is used for representing and satisfying constraints. A constraint logic programming language, called CLP(R), is used for implementing the formulation. The implemented program consists of sixteen rules. These rules are used for both the analysis and partial synthesis of truss structures. Several truss analysis and synthesis examples using the formulation are presented.

Constraint logic programming (CLP) has demonstrated its ability to handle difficult problems coming from operation research. We think that this approach is relevant to perform program analyses too. However, program analysis often requires solvers for second order constraints, i.e. mainly fixpoint equations, that are not available in CLP languages. In this paper, we present, the language Toupie that is designed to solve such constraints. Toupie uses an extension of Bryant's binary decision diagrams to encode relations which makes it possible to handle relations with huge numbers of elements.

CAL: A theoretical background of constraint logic programming and its applications

We have described the constraint logic programming language CS-Prolog. CS-Prolog is written in PROLOG about 1,500 lines. This is a very small as oppose to similar system CLP which is written in C about 12,000 lines, but less efficient than CLP. However, CS-Prolog solves equations and inequations in reasonable time and this paper shows the simple approach to constraint logic programming using PROLOG and this technique is very useful for constraint logic programming language system on top of PROLOG machine.

The concept of Expert Decision Support Systems is based on the integration of Decision Support Systems and Expert Systems, providing the decision maker with features from both types of systems (e.g. simulation, explanations, control of reasoning). Constraint logic programming languages, such as CLP(R) or CHIP, achieve this integration by merging logic programming, a paradigm of Artificial Intelligence and Expert Systems, with constraint solving techniques similar to those used in Operations Research and Decision Support Systems. Their embedded constraint solver extends the expressive power of logic programming languages, most notably on the domain of numerical expressions. The paper illustrates how constraint logic programming may be used in EDSS development by presenting a small classroom scheduling problem developed with CLP(R), and compares this approach to more traditional Operations Research techniques.

In this paper, we present the constraint language Toupie which is a finite domain μ-calculus interpreter that uses extended decision diagrams to represent relations and formulae. “Classical” constraint logic programming languages over finite domains (CLP(FD)) are designed to find one solution to a constraint problem, eventually the best one according to a given criterion. In Toupie, constraints are used to characterize existing relationships between variables. We advocate the use of this paradigm to model and solve efficiently difficult constraint problems that are not tractable with CLP(FD) languages.KeywordsSymbolic Model CheckingConstraint Languages

The main aim of structural engineer is to design the structure for a serviceable, safe, durable and economical. The entire process of structural planning and design is required imagination and sound knowledge. Analysis and design of G+10 storey residential building structure as per IS Code methods. Analysis and design of entire structure have been completed by manual design and verifies using STAAD.PRO V8i Software. Now a day large number of application software’s are available in the civil engineering field. All these software’s are developed as the basis of advanced. Finite element analysis which includes the effect of dynamic load such as wind effect, effect bets etc. in the present work, an attempt has been made to study the efficiency of certain civil engineering applications software’s such as STAAD.PRO V8i and ETABS. All the drafting and detailing was done by using AutoCAD 2021. In this project, the design of beam, column, slab, staircase, shear wall is calculated by “Limit State Method” using IS: 456-2000 IS code book. Different loads active on the member are consider according to IS:875-1987(part1,part2,part-3). Hence residential building is properly planned in accordance with Indian Standard Codes of India. KEY WORDS :- Analysis of structure(G+10) ,Design of structure (G+10), Auto cad 2021 ,STAAD.PRO V8i.

Purpose This research presents a design method for designing greenhouse structures based on topology optimization. Moreover, the structural design of a gothic greenhouse is proposed in which its structural strength has been improved by using this proposed method. In this method, the design of the structure is done mathematically; therefore, in the design process, more attention can be focused on the constraint space and boundary conditions. It was also shown how the static reliability and fatigue coefficients will change as a result of the design of the greenhouse structure with this method. Another purpose of this study is to find the weakest part of the greenhouse structure against lateral winds and other general loads on the greenhouse structure. Design/methodology/approach In the proposed method, the outer surface and the allowable volume as a constraint domain were considered. The desired loads can be located on the constraint domain. The topology optimization was used to minimize the mass and structural compliance as the objective function. The obtained volume was modified for simplifying the construction. The changes in the shape of the greenhouse structure were investigated by choosing three different penalty numbers for the topology optimization algorithm. The final design of the proposed structure was performed based on the total simultaneous critical loads on the structure. The results of the proposed method were compared in the order of different volume fractions. This showed that the volume fraction approach can significantly reduce the weight of the structure while maintaining its strength and stability. Findings Topology optimization results showed different strut and chords composition because of the changes in maximum mass limit and volume fraction. The results showed that the fatigue was more hazardous, and it decreased the strength of structure nearly three times more than a static analysis. Further, it was noticed that how the penalty numbers can affect topology optimization results. An optimal design based on topology optimization results was presented to improve the proposed greenhouse design against destruction and demolition. Furthermore, this study shows the most sensitive part of the greenhouse against the standard loads of wind, snow, and crop. Originality/value The obtained designs were compared with a conventional arch greenhouse, and then the structural performances were shown based on standard loads. The results showed that in designing the proposed structure, the optimized changes increased the structure strength against the standard loads compared to a simple arch greenhouse. Moreover, the stress safety factor and fatigue safety factor because of different designs of this structure were also compared with each other.

The paper describes the design of a virtual reality simulator destined to a robotic system designed for patient's lower limb medical recovery. The VR simulator is created in Unity 5 environment. In this environment was imported the mechanical design of the robotic structure, together with a virtual human model (an avatar) that latter was coupled with the robotic structure. The robotic mechanical structure is designed in the Siemens NX environment, a professional mechatronics design software and the human virtual model was created using the MakeHuman program, an open source 3D computer graphics middleware. In the first step for creating the virtual reality simulator, an enclosure was defined where the robotic structure used to recover the lower limb has been introduced. In the second stage, the human virtual model was loaded into Unity 5 environment and “attached” to the robotic mechanical system. In the last stage was defined a Robotic system User Interface (RUI) for the robotic system control. The RUI was created using C Sharp (C#) programming language that exists within the Visual Studio software package.

ABSTRACTThe present paper delineates a three‐step algorithm for the analytic network process (ANP) structure design. When defining the decision goal and the alternative set, one can use the three‐step algorithm proposed in this paper, first, to specify the decision criteria, and second, to outline the structure of the ANP problem. To ease the process of ANP structure design, we present two novel data structures: the multiple‐effect tree and the multiple‐criteria tree. The multiple‐effect tree helps explore the apparent consequences of a given event or state—known in this paper as the decision alternatives—whereas the multiple‐criteria tree is considered the missing link between the multiple‐effect tree and the ANP structure. Employing the approach presented in this paper will help detect any mistakes in the ANP structure design. A numerical example is provided in the final section of the paper to better articulate the ideas. Copyright © 2011 John Wiley & Sons, Ltd.

This paper presents new techniques in two different areas. Firstly, it proposes a solution to the problem of testing embedded processors. Towards this end, it discusses the automatic generation of executable test programs from a specification of test patterns for processor components. Secondly, the paper shows how constraint logic programming (CLP) improves the software production process for design automation tools. The advantages of CLP languages include: built-in symbolic variables and the built-in support for constraints over finite domains such as integers and Booleans.

The Architecture/Engineering/Construction (AEC) industry is one of the multidisciplinary domains in which collaboration among related parties is of utmost importance1. Despite the intense flow of information between design and LCC (Life Cycle Cost) professionals, there is a lack of research to better understand and manipulate these processes. Architecture design and LCC management is a process of planning a tangible building and cost on a tangible land through intangible work. Due to this characteristic of design work, conventional design management was conducted around the drawings as the final outcome, but actual individual processes of design and LCC (Life Cycle Cost) planning for facility were excluded. As a result, design work and LCC planning completely depended on the individual abilities and experiences of each architect and LCC planner. Even organization of information required for design and LCC process are considered to belong to the domain of individual ability. Therefore, this study proposes an integrated system development methodology of design and LCC process for an information oriented design and LCC management system, which allows architects and LCC planners to easily access information to be provided in each design stage and its relevant LCC planning process, and for design and cost management companies to improve the performance through the systematic storage and usage of data after the completion of an educational project. This research analyzes actual design and LCC processes in currently active companies and proposes a standard design and LCC process, and then examines input and output information for each task in the process in order to propose an information oriented standard design and LCC process. Based on this, Data Flow Diagram (DFD) and Entity Relationship Diagram (ERD) is designed for an information oriented design and LCC management system.