33 research outputs found

    Research in advanced formal theorem-proving techniques

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    The results are summarised of a project aimed at the design and implementation of computer languages to aid in expressing problem solving procedures in several areas of artificial intelligence including automatic programming, theorem proving, and robot planning. The principal results of the project were the design and implementation of two complete systems, QA4 and QLISP, and their preliminary experimental use. The various applications of both QA4 and QLISP are given

    Research and applications: Artificial intelligence

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    The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness

    Decision-making and problem-solving methods in automation technology

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    The state of the art in the automation of decision making and problem solving is reviewed. The information upon which the report is based was derived from literature searches, visits to university and government laboratories performing basic research in the area, and a 1980 Langley Research Center sponsored conferences on the subject. It is the contention of the authors that the technology in this area is being generated by research primarily in the three disciplines of Artificial Intelligence, Control Theory, and Operations Research. Under the assumption that the state of the art in decision making and problem solving is reflected in the problems being solved, specific problems and methods of their solution are often discussed to elucidate particular aspects of the subject. Synopses of the following major topic areas comprise most of the report: (1) detection and recognition; (2) planning; and scheduling; (3) learning; (4) theorem proving; (5) distributed systems; (6) knowledge bases; (7) search; (8) heuristics; and (9) evolutionary programming

    Learning Models in Educational Game Interactions: A Review

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    Educational games have now been used as innovative media and teaching strategies to achieve more effective learning and have an impact that tends to be very good in the learning process. However, it is important to know and systematically prove that the application of the learning model in the interaction of educational games is indeed feasible to be adopted and has an effect. This paper aims to present empirical evidence of the current situation regarding the application of learning models in the flow of educational game interactions. The method used is a systematic literature review by adopting three main stages, namely: 1) Planning; 2) Implementation; 3) Reporting. Then recommend the ten steps in the systematic literature review process along with the selection process through the test-retest approach. The initial search obtained 1,405,310 papers, then go through the selection stage. The selection process took place at stage B1 with the number of papers that successfully passed 198, at the B2 selection stage there were 102 papers, and we focus 75 papers that have passed a fairly rigorous screening and selection process on the quality assessment process for primary studies, used to answer research objectives and questions. We can confirm and conclude that 75 papers have applied the learning model in educational game interactions. The dominating domain is Education, the type of game that dominates is Educational Game, for the most dominating subjects are Programming, Student Learning Motivation as the most dominating impact, Experimental Design as a trial technique, the most widely used evaluation instruments are Questionnaires and Tests, a population that dominates between 79-2,645 people, and 8 papers to support learning in vocational education

    Computer-Aided Decision-Making for Flight Operations: Technical Report Number 2

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    Coordinated Science Laboratory was formerly known as Control Systems LaboratoryAvionics Laboratory, U.S. Air Force Systems Command, Wright-Patterson Air Force Base / AF F33615-73-C-123

    Program conversing in Portugese providing a library service

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    TUGA is a program which converses in Portuguese to provide a library service covering the field of Artificial Intelligence. The objective of designing the program TUGA was the development of a feasible method for consulting and creating data bases in natural Portuguese. The resulting program allows dialogues where the program and its users behave in the way humans normally do in a dialogue setting. The program can answer/ and question in pre-defined scenarios. Users can question/ answer and issue commands in a natural and convenient way/ without bothering excessively with the form of the dialogues and sentences. The original contributions of this work are: the treatment of dialogues. the adaptation of Colmerauer's natural language framework to Portuguese, the particular method for evaluating the logical structures involved in Colmerauer's framework, and the library service application itself. The program is implemented in Prolog, a simple and surprisingly powerful programming language essentially identical in syntax and semantics to a subset of predicate calculus in clausal form

    Automated freeform assembly of threaded fasteners

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    Over the past two decades, a major part of the manufacturing and assembly market has been driven by its customer requirements. Increasing customer demand for personalised products create the demand for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products - or different parts - with the same sets of equipment. Consequently, manufacturing companies have deployed various automation systems and production strategies to improve their resource efficiency and move towards right-first-time production. However, many of these automated systems, which are involved with robot-based, repeatable assembly automation, require component- specific fixtures for accurate positioning and extensive robot programming, to achieve flexibility in their production. Threaded fastening operations are widely used in assembly. In high-volume production, the fastening processes are commonly automated using jigs, fixtures, and semi-automated tools. This form of automation delivers reliable assembly results at the expense of flexibility and requires component variability to be adequately controlled. On the other hand, in low- volume, high- value manufacturing, fastening processes are typically carried out manually by skilled workers. This research is aimed at addressing the aforementioned issues by developing a freeform automated threaded fastener assembly system that uses 3D visual guidance. The proof-of-concept system developed focuses on picking up fasteners from clutter, identifying a hole feature in an imprecisely positioned target component and carry out torque-controlled fastening. This approach has achieved flexibility and adaptability without the use of dedicated fixtures and robot programming. This research also investigates and evaluates different 3D imaging technology to identify the suitable technology required for fastener assembly in a non-structured industrial environment. The proposed solution utilises the commercially available technologies to enhance the precision and speed of identification of components for assembly processes, thereby improving and validating the possibility of reliably implementing this solution for industrial applications. As a part of this research, a number of novel algorithms are developed to robustly identify assembly components located in a random environment by enhancing the existing methods and technologies within the domain of the fastening processes. A bolt identification algorithm was developed to identify bolts located in a random clutter by enhancing the existing surface-based matching algorithm. A novel hole feature identification algorithm was developed to detect threaded holes and identify its size and location in 3D. The developed bolt and feature identification algorithms are robust and has sub-millimetre accuracy required to perform successful fastener assembly in industrial conditions. In addition, the processing time required for these identification algorithms - to identify and localise bolts and hole features - is less than a second, thereby increasing the speed of fastener assembly

    Machine intelligence and robotics: Report of the NASA study group

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    Opportunities for the application of machine intelligence and robotics in NASA missions and systems were identified. The benefits of successful adoption of machine intelligence and robotics techniques were estimated and forecasts were prepared to show their growth potential. Program options for research, advanced development, and implementation of machine intelligence and robot technology for use in program planning are presented

    Large Angle Transient Dynamics (LATDYN) user's manual

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    A computer code for modeling the large angle transient dynamics (LATDYN) of structures was developed to investigate techniques for analyzing flexible deformation and control/structure interaction problems associated with large angular motions of spacecraft. This type of analysis is beyond the routine capability of conventional analytical tools without simplifying assumptions. In some instances, the motion may be sufficiently slow and the spacecraft (or component) sufficiently rigid to simplify analyses of dynamics and controls by making pseudo-static and/or rigid body assumptions. The LATDYN introduces a new approach to the problem by combining finite element structural analysis, multi-body dynamics, and control system analysis in a single tool. It includes a type of finite element that can deform and rotate through large angles at the same time, and which can be connected to other finite elements either rigidly or through mechanical joints. The LATDYN also provides symbolic capabilities for modeling control systems which are interfaced directly with the finite element structural model. Thus, the nonlinear equations representing the structural model are integrated along with the equations representing sensors, processing, and controls as a coupled system
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