Toward an object-oriented and automated approach for achieving robotic assembly

This paper elaborates an object-oriented and automated approach for generating assembly sequences and achieving robotic assembly. This system, built with database and artificial intelligence (AI) techniques, provides the robot with the assembly sequence layout for the automatic handling rule. The critical set of problems is derived from various schemes such as model-based object recognition, features information, geometric and physical constraints between components, knowledge interpretation and robot task sequencing. Pattern recognition regarding shapes and features, along with a knowledge-based assembly, are the key issues of the authors' work. The methodology is shown through two illustrative examples involving different designs of parts in an assembly environment.     

An expert system for design for robotic assembly

In recent years, due to the various advantages associated with automation and robotics, much work has been done in developing robotic systems for assembly operations. Since part design plays a major role in assembly, this paper deals with the design of parts for ease of robotic assembly. Considerable knowledge is available in the form of design for robotic assembly rules. In addition, a large amount of data is required for decisions regarding suitability of parts for robotic assembly. The implementation of design for robotic assembly rules would be much easier with the help of an expert system, which would guide the designer toward choosing the design alternative that can best facilitate ease of assembly from a robotic point of view.To this end, a prototype expert system for design for robotic assembly is developed and presented in this paper. The expert system was implemented as a production system, which consists of rules and Object-Attribute-Value (O-A-V) triplets to represent domain knowledge. In order to best utilize the domain specific knowledge, a state space search-based inference mechanism was employed. The implementation of the prototype system is illustrated with examples.     

A graph-based expert system approach to geometric feature recognition

Geometric feature recognition is a crucial task in the development of concurrent engineering software. This paper presents a new methodology for geometric feature recognition which combines the advantages of face-edge adjacency graphs and expert systems. The methodology uses several new concepts such as enhanced winged edge data structure (EWEDS) and multi-attributed adjacency graphs (MAAG). The object model is presented as a set of facts. The rules for the recognition of each feature are derived from the corresponding feature-MAAG. This simplifies the process of writing the rules while enabling the inclusion of new features into the rule base as they are encountered.     

An experiment for truly parallel logic programming

A truly parallel logic programming system is proposed. The system is based on the commercially available parallel logic programming language STRAND, which has been extended in order to overcome the inherent limitations of such systems, like AND-type of parallelism, lack of backtracking, limited unification, etc. The system has been tested using an example from the area of natural language processing.     

ADA: A language for robot programming?

Robot programming languages are emerging from their experimental stage and entering an assessment phase. Their main features are illustrated and a parallel with ADA is proposed. The comparison is positive for ADA, in the sense that ADA provides most of the required capabilities. The ability of reasoning on object models and taking decisions will play an increasing role in the future. In this case the role of ADA would possibly change and its interest as robot programming language decrease.     

DISLOG: programming in logic with discontinuities

In this paper, we present an extension to PROLOG we call DISLOG which is designed to deal with relations between non-contiguous elements in a structure. This extension turns out to be well suited for syntactic analysis of natural and artificial languages. It is also well adapted to express traversal constraints in applications such as planning and expert systems and deductive systems involving, for example, temporal reasoning, DISLOG belongs to the constrained logic programming paradigm and turns out to be more declarative, transparent, and simple than PROLOG to deal with longdistance relations.     

基于Linux系统分析计算机C语言编程技巧

C语言程序设计是高效计算机专业学生必修的一门基础课程,同时也是后续课程的入门课程,对于掌握基本计算机技术有着重要意义。尤其在Linux系统下,该系统在所有操作系统中占着重要地位,如何掌握计算机C语言编程技巧是当务之急。为此,本文重点探讨基于Linux系统分析计算机C语言编程技巧。     

Using classes as specifications for automatic construction of programs in the NUT system

It is shown, how the object-oriented programming paradigm has been combined with automatic program construction in the NUT system: type information extracted from a class specification is being used for automatic construction of methods for the class. Special compute-messages are introduced as requests for program synthesis which can be done statically or dynamically. Particular features of the specification language which support the program synthesis are considered and applications of this method are outlined.     

Algorithm recognition for programming tutoring based on flow graph parsing

Plan-recognition with template matching shows reasonable performance for recognizing general control structures. However, problems containing well-defined algorithms such as sorting and searching are difficult to recognize by the template-based methodology alone, because an algorithm is often highly optimized and therefore hard to divide into smaller meaningful units. Based on this observation, we propose an algorithm recognition methodology to augment the plan-recognition approach.Our algorithm recognition approach is based on the flow graph parsing which performs a partial recognition of programs. The methodology is extended to completely understand algorithm implementations by providing the information of the program's goal, a specification of programming assignment in tutoring environment. Utilization of goal information is two-fold; extending the role of transformation rules to represent algorithm-specific information and looking for salient graph parts of algorithm plan to determine which has been used to implement the goal. Preliminary evaluation was performed on students' programs containing sort algorithm.     

Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models

Two-sided assembly lines are especially used at the assembly of large-sized products, such as trucks and buses. In this type of a production line, both sides of the line are used in parallel. In practice, it may be necessary to optimize more than one conflicting objectives simultaneously to obtain effective and realistic solutions. This paper presents a mathematical model, a pre-emptive goal programming model for precise goals and a fuzzy goal programming model for imprecise goals for two-sided assembly line balancing. The mathematical model minimizes the number of mated-stations as the primary objective and it minimizes the number of stations as a secondary objective for a given cycle time. The zoning constraints are also considered in this model, and a set of test problems taken from literature is solved. The proposed goal programming models are the first multiple-criteria decision-making approaches for two-sided assembly line balancing problem with multiple objectives. The number of mated-stations, cycle time and the number of tasks assigned per station are considered as goals. An example problem is solved and a computational study is conducted to illustrate the flexibility and the efficiency of the proposed goal programming models. Based on the decision maker's preferences, the proposed models are capable of improving the value of goals.     

Experiments with service-oriented architectures for industrial robotic cells programming

Integration of equipment in industrial robot cells is to an increasing part involved with interfacing modern Ethernet technologies and low-cost mass produced devices, such as vision systems, laser cameras, force–torque sensors, soft-PLCs, digital pens, pocket-PCs, etc. This scenario enables integrators to offer powerful and smarter solutions, more adapted to small and medium enterprises (SMEs), capable of integrating process knowledge and interface better with humans. Nevertheless, programming all these devices efficiently requires too much specific knowledge about the devices, their hardware architectures and specific programming languages, details about system communication low-level protocols, and other tricky details at the system level. To address these issues, this paper describes and analyses two of the most interesting service-oriented architectures (SOA) available, which exhibit characteristics that are well adapted to industrial robotics cells. To compare, discuss and evaluate their programming features and applicability a test bed was specially designed, and the two SOA are fully implemented to program the test bed. Special focus is given to the way services are specified and to the orchestration tools used to manage system logic. The obtained results show clearly that using integrations schemes based on SOA reduces system integration time and are more adapted to industrial robotic cell system integrators.     

Message-Based Evaluation in Scheme for High-Level Robot Control

In this paper, we present a method for high-level control of robots whose low-level software is based on dynamically reconfigurable, reusable real-time software modules. Our approach is to use an embedded interpreter for a general-purpose programming language to direct the operation of the low-level modules toward meeting the task-level goals of the robot. To this end, we present RSK, a virtual-machine kernel implementing a Scheme interpreter capable of hard real-time operation, and employing a method of code execution we call message-based evaluation (MBE) . MBE is a novel combination of a traditional code execution model and a message-passing architecture, which simplifies the process of writing code for managing the robot's reconfigurable subsystem.     

A metalogic programming approach: language,semantics and applications

Abstract

This paper presents a logic programming language of novel conception, called Reflective Prolog, which allows declarative metaknowledge representation and metareasoning. The language is defined by augmenting pure Prolog (Horn clauses) with capabilities of self-reference and logical reflection. Self-reference is designed as a quotation device (a carefully defined naming relation) which allows the construction of metalevel terms that refer to object-level terms and atoms. Logical reflection is designed as an unquotation mechanism (a distinguished truth predicate) which relates names to what is named, thus extending the meaning of domain predicates. The reflection mechanism is embodied in an extended resolution procedure which automatically switches the context between levels. This implicit reflection relieves the programmer from having to explicitly deal with control aspects of the inference process. The declarative semantics of a Reflective Prolog definite program P is provided in terms of the least reflective Herbrand model of P, characterized by means of a suitable mapping defined over the Herbrand interpretations of P. The extended resolution is proved sound and complete with respect to the least reflective Herbrand model. By illustrating Reflective Prolog solutions to an organic set of problems, and by discussing the main differences with respect to other approaches to logic metaprogramming, we show that the proposed language deploys, within its field of action, greater expressive and inferential power than those available till now. The interpreter of the language has been fully implemented. Because of its enhanced power, logic semantics and working interpreter, Reflective Prolog is offered as a contribution toward making the declarative approach of logic programming applicable to the development of increasingly sophisticated knowledge-based systems.     

CEPROL: A cellular programming language

Realized cellular automata may be operated by universal computer systems as programmable special-purpose processors for parallelizable problems. Because of their architecture (local neighbourhood, small storage size per cell, they are well suited for processing systolic algorithms. A cellular programming language — named CEPROL — is presented which offers means for programming and controlling cellular automata processing such algorithms.     

Type II robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model

In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The aim is to minimize the cycle time, robot setup costs and robot costs. The second difference is on the procedure proposed to solve the problem. In addition, a new mixed-integer linear programming model is developed. Since the problem is NP-hard, three versions of multi-objective evolution strategies (MOES) are employed. Numerical results show that the proposed hybrid MOES is more efficient.     

Annotated Logic Applications for Imperfect Information

Imperfect information is a very general term that comprises different types of information, such as uncertain, vague, fuzzy, inconsistent, possibilistic, probabilistic, partially or totally incomplete information [2]. In the literature of knowledge representation we find a different formal model for each one of these distinct types. For example, annotated logic is a formal model to represent inconsistent information.Annotated logics are non-classical logics introduced in [20] as a logic programming theory. They were proved to be paraconsistent. Based on [5], we present in this work the annotated logic programming theory and some of its applications in Artificial Intelligence (AI). We present it as a formalism to reason with inconsistent information and investigate its possibility to represent other types of imperfect information, such as possibilistic and non-monotonic reasoning. Our main goal is to verify and confirm the importance of annotated logics as a tool for developing knowledge-based and automated reasoning systems in AI.     

Experiences in database system implementation using a persistent programming language

The EXODUS database toolkit, and in particular the E persistent programming language, have been used in two substantial database system implementation efforts by the authors, the Ariel database rule system and the Triton nested relation DBMS. An important advantage of using a persistent programming language for database system implementation is that it is easy to implement special-purpose persistent objects used by the DBMS such as catalogs, rule indexes, and nested relational structures. Support for transactions built into a persistent programming language greatly reduces the effort required to implement a database system. A disadvantage observed is that it is not possible to map the type system of the DBMS to the type system of the underlying programming language while still retaining good performance for ad hoc queries. Also, software engineering difficulties arise when a persistent language makes a distinction between database types and main-memory types.     

基于云平台的智能语音交互机器人设计

现有的语音交互机器人多采用用户提问、机器人回答的单向交流方式,人机交互的智能性和灵活性较差.本文研究运用树莓派(Raspberry Pi)计算机和配套的语音板作为硬件载体,融合语音唤醒、语音识别、语音合成、自然语言处理等人工智能技术,调用科大讯飞开放云平台、在线图灵机器人,搭建一种基于云平台的智能语音交互机器人系统,并...     

Granularity issues in a knowledge-based programming environment

Marvel is a knowledge-based programming environment that assists software development teams in performing and coordinating their activities. While designing Marvel, several granularity issues were discovered that have a strong impact on the degree of intelligence that can be exhibited, as well as on the friendliness and performance of the environment. The most significant granularity issues include the refinement of software entities in the software database and decomposition of the software tools that process the entities and report their results to the human users. This paper describes the many alternative granularities and explains the choices made for Marvel.     

Parallel programming: An axiomatic approach

This paper develops some ideas expounded in [1]. It distinguishes a number of ways of using parallelism, including disjoint processes, competition, cooperation, and communication. In each case an axiomatic proof rule is given.