Remote Access to a Prototyping Laboratory

There is a growing global demand for continuing adult higher education particularly in science and engineering subjects. New technologies are emerging which would enable the development of a Remote Access Laboratory for rapid prototyping of Artificial Intelligence, as a learning environment for mechatronic engineering, in which high precision electromechanical devices are designed to exhibit autonomous behaviour. Secondary research investigated the learning theories for a Remote Access Laboratory, and the current practices for distance learning, involving groupware in shared activity 'collaboratories'. Having determined that the laboratory would need a multi-user interactive environment architecture, with the requirement for adaptability to rapid developments,a distributed software architecture was selected. The laboratory design was subsequently argued to be best served by Intelligent Agents in a Multi-Agent system. The aims of the research were to establish the viability of a Remote Access Laboratory for mechatronic experimentation, and to evaluate the technologies required to implement such a laboratory environment for rapid prototyping. These were achieved by developing a novel user interface, based on a multi-functional screen layout, and a graphical specification facility to provide robotic navigation that is intuitive to use and does not require text-based programming. The research investigated the prototyping of robotic behaviour, which used Programming by Demonstration as an innovative technique to prototype robot navigation. The method of designing behaviours met an anticipated need to allow the robot to interact with an environment, to achieve goals under conditions of uncertainty, while requiring a level of abstraction in the behaviour design. The interface structured a composite of the designed behaviours into prototype Artificial Intelligence using a hierarchical behaviour architecture, which complied with the principles of Object Orientated programming. This was subsequently a new and original programming method to facilitate rapid prototyping of Artificial Intelligence design and structuring. Experimentation involved 20 participants attempting to accomplish a series of tasks which involved using the prototyped interface and an existing text-based robot programming system. The participants were profiled by their formal qualifications, knowledge and experience. The experimental data obtained were used to establish a comparative measure of the prototype interface success compared with an existing distance-learning, home experiment kit, in the form of a small controllable model vehicle. The data obtained provided strong evidence to support the hypothesis that a Programming by Demonstration based system for rapid prototyping is more flexible and easier to use than a previously existing distance learning text-based system. The Programming by Demonstration system showed great promise, being quicker for prototyping, and more intuitive. The learning interface design pioneered new techniques and technologies for rapid prototyping of Artificial Intelligence in a Mechatronics Remote Access Laboratory

Real-time application of knowledge-based systems

The Rapid Prototyping Facility (RPF) was developed to meet a need for a facility which allows flight systems concepts to be prototyped in a manner which allows for real-time flight test experience with a prototype system. This need was focused during the development and demonstration of the expert system flight status monitor (ESFSM). The ESFSM was a prototype system developed on a LISP machine, but lack of a method for progressive testing and problem identification led to an impractical system. The RPF concept was developed, and the ATMS designed to exercise its capabilities. The ATMS Phase 1 demonstration provided a practical vehicle for testing the RPF, as well as a useful tool. ATMS Phase 2 development continues. A dedicated F-18 is expected to be assigned for facility use in late 1988, with RAV modifications. A knowledge-based autopilot is being developed using the RPF. This is a system which provides elementary autopilot functions and is intended as a vehicle for testing expert system verification and validation methods. An expert system propulsion monitor is being prototyped. This system provides real-time assistance to an engineer monitoring a propulsion system during a flight

The Effect of Jetting Parameters on the Performance of Droplet Formation for Ink-Jet Rapid Prototyping

Heinzl et al. (1985) reports that experiments in ink-jets to produce drawings or signals occurred as early as 1930. Various companies such as IBM and Pitney-Bowes have conducted extensive studies on these devices for many years. Many such reports are available in such journals as the IBM Journal of Research and Development. While numerous articles have been published on the jetting characteristics of ink and water, the literature is rather limited on fluids such as waxes (Gao & Sonin 1994) or non-water based fluids (Passow, et al. 1993). This present study extends the knowledge base to determine the performance of molten waxes in "ink-jet" type printers for rapid prototyping. The purpose of this research was to qualitatively and quantitatively study the droplet formation of a drop-on-demand ink-jet type nozzle system for rapid prototyping

Case acquisition from text: ontology-based information extraction with SCOOBIE for myCBR

myCBR is a freely available tool for rapid prototyping of similarity-based retrieval applications such as case-based product recommender systems. It provides easy-to-use model generation, data import, similarity modelling, explanation, and testing functionality together with comfortable graphical user interfaces. SCOOBIE is an ontology-based information extraction system, which uses symbolic background knowledge for extracting information from text. Extraction results depend on existing knowledge fragments. In this paper we show how to use SCOOBIE for generating cases from texts. More concrete we use ontologies of the Web of Data, published as so called Linked Data interlinked with myCBR’s case model. We present a way of formalising a case model as Linked Data ready ontology and connect it with other ontologies of the Web of Data in order to get richer cases

A comparison of languages which operationalise and formalise {KADS} models of expertise

In the field of Knowledge Engineering, dissatisfaction with the rapid-prototyping approach has led to a number of more principled methodologies for the construction of knowledge-based systems. Instead of immediately implementing the gathered and interpreted knowledge in a given implementation formalism according to the rapid-prototyping approach, many such methodologies centre around the notion of a conceptual model: an abstract, implementation independent description of the relevant problem solving expertise. A conceptual model should describe the task which is solved by the system and the knowledge which is required by it. Although such conceptual models have often been formulated in an informal way, recent years have seen the advent of formal and operational languages to describe such conceptual models more precisely, and operationally as a means for model evaluation. In this paper, we study a number of such formal and operational languages for specifying conceptual models. In order to enable a meaningful comparison of such languages, we focus on languages which are all aimed at the same underlying conceptual model, namely that from the KADS method for building KBS. We describe eight formal languages for KADS models of expertise, and compare these languages with respect to their modelling primitives, their semantics, their implementations and their applications. Future research issues in the area of formal and operational specification languages for KBS are identified as the result of studying these languages. The paper also contains an extensive bibliography of research in this area

Product Focused Freeform Fabrication Education

Presented in this paper is our experience of teaching freeform fabrication to students at the Missouri University of Science and Technology, and to high school students and teachers. The emphasis of the curriculum is exposing students to rapid product development technologies with the goal of creating awareness to emerging career opportunities in CAD/CAM. Starting from solid modeling, principles of freeform fabrication, to applications of rapid prototyping and manufacturing in industry sponsored product development projects, students can learn in-depth freeform fabrication technologies. Interactive course content with hands-on experience for product development is the key towards the success of the program.Mechanical Engineerin

Initial thoughts on rapid prototyping techniques

This paper sets some context, raises issues, and provides our initial thinking on the characteristics of effective rapid prototyping techniques.After discussing the role rapid prototyping techniques can play in the software lifecycle, the paper looks at possible technical approaches including: heavily parameterized models, reusable software, rapid prototyping languages, prefabrication techniques for system generation, and reconfigurable test harnesses.The paper concludes that a multi-faceted approach to rapid prototyping techniques is needed if we are to address a broad range of applications successfully -- no single technical approach suffices for all potentially desirable applications

A Knowledge-based Decision Support System for RP&M Process Selection

Due to the large variety of RP&M material/machines and the. strengths/weaknesses associated with different RP&M processes, the decision·to select a suitableRP&M system becomes increasingly difficult. This paper presents a knowledge-based approach for the selection ofsuitable RP&M material/machine to meet specific. requirements ofRP&Mapplications. The system receives input data on the CAD modelandthe user's specifications,andgenerates outputs that provide the most appropriate combination ofRP&Mmaterial/machine.·Optimal orientations, together with estimated manufacturing time and cost, are considered and given in the final outcome to help the user make the choice.Mechanical Engineerin

The Express Project: Automating the Software Development Process

The goal of the Express project is to provide an efficient software development environment for embedded systems. The approach is to create a new life-cycle paradigm, using rapid prototyping to validate system specifications. The rapid prototype will be made possible by using (1) very high level specification languages that automatically generate code and (2) a user-machine interface that helps both in the layout of the design and in the specification of the input devices and output screens for the embedded system. All user interactions with Express are integrated through Express\u27s knowledge-based Framework, which will support efficient, interdisciplinary communications. The Framework is designed to support evolutionary prototyping. The high-level view of the embedded system can be created and evolved concurrently with the low-level specifications of processing segments that are understood and known to be required. System engineers will define the high-level view (including allocation of requirements from layer to layer), and specialists will create low-level diagrams and specifications for processing threads in each of their (initially) independent areas. In small steps the two views will be merged into a single architecture diagram. One can zoom in on one subsystem and be presented with the fine structure of the subsystem down to the level of executable specifications. A second subsystem, which is reached through the knowledge-based Framework, is the Graphical Specification Subsystem (GSS) for Displays. It will make human-machine interface engineers more productive when designing operator displays for embedded systems. It will allow them to build a display graphically. They can select icons from a menu, position and size each instance of an icon graphically (by mouse action), and specify in a natural way the desired interaction with other portions of the embedded system. Gauges, graphs, and maps are examples of objects represented by icons. The GSS also will be used to specify simulated input devices to the system, such as mice, push buttons, and joysticks