Prof. Dr. Ing. Frank Petzold + Gerhard Schubert "Collaborative Design Platform"

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Martin Centre Research Seminar Series

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Abstract The motivation behind the interdisciplinary research project "Collaborative Design Platform" (CDP) is to resolve the current discrepancy between analogue ways of working in the early urban design stages and the ever-increasing use of digital tools in office pratice. By directly linking familiar, analogue ways of working with digital computer aided design tools, the CDP represents a working environment that allows designers to work the way that they are used to, while making use of the potential of computers. The platform creates a direct connection between physical volumetric models and interactive digital content using a large-format multi-touch table as a work surface combined with real-time 3D scanning. Combining the 3D data from the scanned model with the 3D digital GIS environment model makes it possible to computer design relevant simulations and analyses. These are displayed in real-time on the working model to help architects assess and substantiate their design decisions. Biography Frank Petzold's research and teaching activities cover the entire spectrum of IT-supported architectural design and planning. He has contributed more than 50 papers and articles to conferences and professional journals. As part of the Collaborative Research Centre project, "Materials and constructions for the renovation of building structures", funded by the DFG (German Research Foundation), he examined architectural design in existing built contexts and the structured capture of data for building information modelling (BIM). In the DFG-funded "AR Cave - projection-based technology for on-site surveying, visualisation and simulation" research project, augmented reality methods were employed for working directly within existing built contexts. The "KREMLAS - Development of a creative evolutionary design method for layout problems in architecture and urban design" research project (also funded by the DFG) examines approaches for assessing solutions produced using evolutionary methods.