A new and systematic approach to machine vision-based robot manipulation of deformable (non-rigid) linear objects is introduced. This approach reduces the computational needs by using a simple state-oriented model of the objects. These states describe the relation of the object with respect to an obstacle and are derived from the object image and its features. Therefore, the object is segmented from a standard video frame using a fast segmentation algorithm. Several object features are presented which allow the state recognition of the object while being manipulated by the robot.
A growing share of all software development project work is being done by geographically distributed teams. To satisfy shorter product design cycles, expert team members for a development project may need to be r ecruited globally. Yet to avoid extensive travelling or r eplacement costs, distributed project work is preferred. Current-generation software engineering tools and ass ociated systems, processes, and methods were for the most part developed to be used within a single enterprise. Major innovations have lately been introduced to enable groupware applications on the Internet to support global collaboration. However, their deployment for distributed software projects requires further research. In partic ular, groupware methods must seamlessly be integrated with project and product management systems to make them attractive for industry. In this position paper we outline the major challenges concerning distributed (virtual) software projects. Based on our experiences with software process modeling and enactment environments, we then propose approaches to solve those challenges.
We present two techniques for reasoning from cases to solve classification tasks: Induction and case-based reasoning. We contrast the two technologies (that are often confused) and show how they complement each other. Based on this, we describe how they are integrated in one single platform for reasoning from cases: The Inreca system.
MOLTKE is a research project dealing with a complex technical application. After describing the domain of CNCmachining centers and the applied KA methods, we summarize the concrete KA problems which we have to handle. Then we describe a KA mechanism which supports an engineer in developing a diagnosis system. In chapter 6 weintroduce learning techniques operating on diagnostic cases and domain knowledge for improving the diagnostic procedure of MOLTKE. In the last section of this chapter we outline some essential aspects of organizationalknowledge which is heavily applied by engineers for analysing such technical systems (Qualitative Engineering). Finally we give a short overview of the actual state of realization and our future plans.
In this paper we will present a design model (in the sense of KADS) for the domain of technical diagnosis. Based on this we will describe the fully implemented expert system shell MOLTKE 3.0, which integrates common knowledge acquisition methods with techniques developed in the fields of Model-Based Diagnosis and Machine Learning, especially Case-Based Reasoning.
Within this paper we focus on both the solution of real, complex problems using expert system technology and the acquisition of the necessary knowledge from a case-based reasoning point of view. The development of systems which can be applied to real world problems has to meet certain requirements. E.g., all available information sources have to be identified and utilized. Normally, this involves different types of knowledge for which several knowledge representation schemes are needed, because no scheme is equally natural for all sources. Facing empirical knowledge it is important to complement the use of manually compiled, statistic and otherwise induced knowledge by the exploitation of the intuitive understandability of case-based mechanisms. Thus, an integration of case-based and alternative knowledge acquisition and problem solving mechanisms is necessary. For this, the basis is to define the "role" which case-based inference can "play" within a knowledge acquisition workbench. We will discuss a concrete casebased architecture, which has been applied to technical diagnosis problems, and its integration into a knowledge acquisition workbench which includes compiled knowledge and explicit deep models, additionally.
Today, the worlds and terminologies of mechanical engineering and software engineering coexist, but they do not always work together seamlessly. Both worlds have developed their own separate formal vocabulary for expressing their concepts as well as for capturing and communicating their respective domain knowledge. But, these two vocabularies are not unified, interwoven, or at least interconnected in a reasonable manner. Thus, the subject of this paper is a comparison of the vocabularies of the two fields, namely feature technology from the area of mechanical engineering and software design patterns from the software engineering domain. Therefore, a certain amount of definitions, history, examples, etc. is presented for features as well as for design patterns. After this, an analysis is carried out to identify analogies and differences. The main intention of this paper is to inform both worlds - mechanical and software engineering - about the other side's terminology and to start a discussion about potential mutual benefits and possibilities to bridge the gap between these two worlds, e.g. to improve the manageability of CAx product development processes.
PANDA is a run-time package based on a very small operating system kernel which supports distributed applications written in C++. It provides powerful abstractions such as very efficient user-level threads, a uniform global address space, object and thread mobility, garbage collection, and persistent objects. The paper discusses the design ration- ales underlying the PANDA system. The fundamental features of PANDA are surveyed, and their implementation in the current prototype environment is outlined.
Distributed systems are an alternative to shared-memorymultiprocessors for the execution of parallel applications.PANDA is a runtime system which provides architecturalsupport for efficient parallel and distributed program-ming. PANDA supplies means for fast user-level threads,and for a transparent and coordinated sharing of objectsacross a homogeneous network. The paper motivates themajor architectural choices that guided our design. Theproblem of sharing data in a distributed environment isdiscussed, and the performance of appropriate mecha-nisms provided by the PANDA prototype implementation isassessed.