3 research outputs found

    3D object comparison with geometric guides for Interactive Evolutionary CAD

    Get PDF
    © 2017 The authors and IOS Press. All rights reserved. 3D object comparison is presented as part of research into guided evolutionary Computer-Aided Design (CAD). CAD technology in development will combine human interaction and geometric optimization, within an existing evolutionary design system (EvoShape). Geometric Guides consist of simple 3D target objects (bounding volumes), to which evolving forms are compared. Before comparison, objects must be aligned and scaled, a process known as Pose Normalization (PN) in the literature. Both PN and object comparison have been implemented using standard geometric functions, enabling populations of evolving forms to be directed by the Geometric Guides. The algorithms and their implementation are presented alongside early results and analysis, discussion on limitations and robustness, and their suitability for Interactive Evolutionary CAD

    3D alignment for interactive evolutionary design

    Get PDF
    3D model alignment (‘Pose Normalization’ in the literature) is investigated as part of wider research into guided evolutionary Computer-Aided Design. CAD technology in development will combine human interaction and geometric optimization, within an evolutionary design system. Evolving shapes will be influenced by simple pre-set geometric fuzzy-constraints – internal voids and external bounding geometry created by users. To compare evolving candidate shapes with these pre-set constraints they must first be aligned (rotated, scaled, and co-located). A shortlist of five promising alignment techniques is described. Benchmark data generated using standard CAD functions (centre of gravity, principle axes etc.) will be presented at the conference

    Geometric guides for interactive evolutionary design

    Get PDF
    This thesis describes the addition of novel Geometric Guides to a generative Computer-Aided Design (CAD) application that supports early-stage concept generation. The application generates and evolves abstract 3D shapes, used to inspire the form of new product concepts. It was previously a conventional Interactive Evolutionary system where users selected shapes from evolving populations. However, design industry users wanted more control over the shapes, for example by allowing the system to influence the proportions of evolving forms. The solution researched, developed, integrated and tested is a more cooperative human-machine system combining classic user interaction with innovative geometric analysis. In the literature review, different types of Interactive Evolutionary Computation (IEC), Pose Normalisation (PN), Shape Comparison, and Minimum-Volume Bounding Box approaches are compared, with some of these technologies identified as applicable for this research. Using its Application Programming Interface, add-ins for the Siemens NX CAD system have been developed and integrated with an existing Interactive Evolutionary CAD system. These add-ins allow users to create a Geometric Guide (GG) at the start of a shape exploration session. Before evolving shapes can be compared with the GG, they must be aligned and scaled (known as Pose Normalisation in the literature). Computationally-efficient PN has been achieved using geometric functions such as Bounding Box for translation and scaling, and Principle Axes for the orientation. A shape comparison algorithm has been developed that is based on the principle of non-intersecting volumes. This algorithm is also implemented with standard, readily available geometric functions, is conceptually simple, accessible to other researchers and also offers appropriate efficacy. Objective geometric testing showed that the PN and Shape Comparison methods developed are suitable for this guiding application and can be efficiently adapted to enhance an Interactive Evolutionary Design system. System performance with different population sizes was examined to indicate how best to use the new guiding capabilities to assist users in evolutionary shape searching. This was backed up by participant testing research into two user interaction strategies. A Large Background Population (LBP) approach where the GG is used to select a sub-set of shapes to show to the user was shown to be the most effective. The inclusion of Geometric Guides has taken the research from the existing aesthetic focused tool to a system capable of application to a wider range of engineering design problems. This system supports earlier design processes and ideation in conceptual design and allows a designer to experiment with ideas freely to interactively explore populations of evolving solutions. The design approach has been further improved, and expanded beyond the previous quite limited scope of form exploration
    corecore