Colloquia

Samenvatting

This study focuses on the research and realization of Hybrid Design Tools (HDTs) with real-time feedback and is done for Rawshaping Technology (RST). The goal and objective of RST is the research and development of HDTs for design engineering processes (DEPs). HDTs aim to bridge the gap between the analogue and digital realms of DEPs. Physical and tangible objects offer rich experiences and valuable information to designers and engineers in terms of enhancement of understanding, creating insight and unanticipated information. On the other hand, digital and virtual worlds provide new possibilities. Think of communication technologies, fast and easy processing of data and understanding the world in new ways. HDT(E)s are a means to create a synergy between both worlds.

RST focused mainly on the hybrid realm, incorporating physicality and tangibility in conjunction with virtuality combined within design tools and systems. This study investigates and explores HDTs from a different perspective, to incorporate machine learning and automatic support intelligence. A main research question was, is it possible to incorporate computational feedback systems into HDTs?

This study resulted in the realization of a prototypical hybrid tool and an assistive system (PTs), several iterative user interfaces (UIs), interaction modalities, and a series of tests and experimentation with the final PT. The design problem and -task is narrowed down to design and engineer truss structures (e.g. bridge, crossover). The final PT is a Hybrid Truss Design Tool (HTDT) (Fig. 01). With the HTDT a truss layout can be constructed through organising and manipulating tangible nodes. The HTDT recognises (i.e. machine vision) the nodes as a truss structure and augments information through a virtual representation (i.e. artificial intelligence). By reorganising the nodes and making lots of captures, the user goes through an iterative and creative DEP to find truss layouts that fit his or her design ideas and conceived requirements (Fig. 02).

The HTDT is tested with twenty participants (n=20) based on the above described design task and -problem. The test focused on interaction design (IxD), user experience (UX) and user engagement (UE). Metrics and data were acquired on performance, usability and interactive parameters, for example, constructing, iterating and optimising truss layouts through solution finding and generative problem solving. Users mentioned speediness, playfulness and ease-of-use and other relevant UX aspects which align with RST framework and requirements. Future work is to explore more complex truss problems and/or more advanced computational feedback systems in HDT(E)s.