This paper proposes an aesthetic-driven evolutionary algorithm for user-centered design. The evolutionary algorithm is based on a genetic algorithm (GA). It is developed to work as an art form generator that enhances user's productivity and creativity through reproduction, evaluation, and selection. Users can input their preferences and guide the generating direction to the system. A two-step fitness function is developed to evaluate morphology and aesthetics of the generated art forms. Fractals created by an iterated function system are used for representing art forms in our process. Algorithmic aesthetics are developed based on the aesthetic measure theory, surveys of human preferences, and popular long-lasting symbols. The algorithmic aesthetics is used for evaluating aesthetics of art forms together with subjective nonquantifiable aspects, and placed in the fitness function. The GA basically creates two-dimensional art forms. However, any twodimensional image can be included through the property of a condensation set of fractals. The proposed GA can increase design productivity by about 80%. Examples of jewelry designs and physical prototypes created by the proposed system are included.
Computing accessibility information from a NURBS model is an interesting aspect in design and manufacturing planning. We propose an approach how to compute the accessibility information from a NURBS model, called a polyhedral-based approach. In this paper, not only global point accessibility (usually used in the applications of CMM measuring and machining) but also global patch accessibility (i.e. a new term for mold design) is alternatively determined. At the high resolution, this approach runs faster than the approach for computing the facet accessibility.
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