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  • 1.
    Amadori, Kristian
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Tarkian, Mehdi
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Krus, Petter
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, The Institute of Technology.
    Flexible and Robust CAD Models for Design Automation2012In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 26, no 2, p. 180-195Article in journal (Refereed)
    Abstract [en]

    This paper explores novel methodologies for enabling Multidisciplinary Design Optimization (MDO) of complex engineering products. To realize MDO, Knowledge Based Engineering (KBE) is adopted with the aim of achieving design reuse and automation. The aim of the on-going research at Linköping University is to shift from manual modelling of disposable geometries to Computer Aided Design (CAD) automation by introducing generic high-level geometry templates. Instead of repeatedly modelling similar instances of objects, engineers should be able to create more general models that can represent entire classes of objects. The proposed methodology enables utilization of commercial design tools, hence taking industrial feasibility into consideration. High Level CAD templates (HLCt) will be proposed and discussed as the building blocks of flexible and robust CAD models, which in turn enables high-fidelity geometry in the MDO loop. Quantification of the terms flexibility and robustness is also presented, providing a means to measure the quality of the geometry models. Finally, application examples are presented in which the outlined framework is evaluated. The applications have been chosen from three ongoing research projects aimed at automating the design of transport aircraft, industrial robots, and micro air vehicles.

  • 2.
    Heintz, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Bridging the sense-reasoning gap: DyKnow - Stream-based middleware for knowledge processing2010In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 24, no 1, p. 14-26Article in journal (Refereed)
    Abstract [en]

    Engineering autonomous agents that display rational and goal-directed behavior in dynamic physical environments requires a steady flow of information from sensors to high-level reasoning components. However, while sensors tend to generate noisy and incomplete quantitative data, reasoning often requires crisp symbolic knowledge. The gap between sensing and reasoning is quite wide, and cannot in general be bridged in a single step. Instead, this task requires a more general approach to integrating and organizing multiple forms of information and knowledge processing on different levels of abstraction in a structured and principled manner. We propose knowledge processing middleware as a systematic approach to organizing such processing. Desirable properties are presented and motivated. We argue that a declarative stream-based system is appropriate for the required functionality and present DyKnow, a concrete implemented instantiation of stream-based knowledge processing middleware with a formal semantics. Several types of knowledge processes are defined and motivated in the context of a UAV traffic monitoring application. In the implemented application, DyKnow is used to incrementally bridge the sense-reasoning gap and generate partial logical models of the environment over which metric temporal logical formulas are evaluated. Using such formulas, hypotheses are formed and validated about the type of vehicles being observed. DyKnow is also used to generate event streams representing for example changes in qualitative spatial relations, which are used to detect traffic violations expressed as declarative chronicles.

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