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Thesis in progress de

Thesis in progress
Group : Human-Centered Computing

CAD Modification Techniques for Design Reviews on Heterogeneous Interactive Systems

Starts on 01/10/2015
Advisor : FLEURY, Cédric

Funding :
Affiliation : vide
Laboratory : LIMSI et LRI - HCC

Defended on 08/11/2019, committee :
Mr. Thierry DUVAL, Professor, IMT Atlantique, Brest, France | Reviewer
Mr. Theodore LIM, Associate Professor, Heriot-Watt University, UK | Reviewer
Mrs. Caroline APPERT, Research Director, ILDA team & LRI-HCC, Inria & CNRS, Université Paris-Sud, France | Examiner
Mr. Jean-Claude MARTIN, Professor, CPU team, LIMSI/CNRS, Université Paris-Sud, France | Examiner
Mr. Regis KOPPER, Associate Professor, Duke University, USA | Examiner
Mr. Alexis PALJIC, Associate Professor, MINES ParisTech, France | Examiner
Mr. Patrick BOURDOT, Research Director, VENISE team, LIMSI/CNRS, Université Paris-Sud, France | PhD supervisor
Mr. Cédric FLEURY, Associate Professor, Ex Situ team & LRI-HCC, Inria & CNRS, Université Paris-Sud, France | PhD co-advisor
Mr. Nicolas LADEVEZE, Research Engineer, P2I support team, LIMSI/CNRS, Université Paris-Sud, France | Invited

Research activities :

Abstract :
Industrial design reviews benefit from emerging interactive technologies to become more Realistic, Immersive and Collaborative. The industrial product review is a vital process for project members to assess aesthetic properties, user satisfaction, and technical feasibility of the product before physical prototyping. Particularly, reviewing digital mock-ups in a realistic context with one-to-one scale enriches their reviewing experience, and a shared workspace facilitates discussions across distinct experts. However, modifying the product data during the reviews is still challenging. Although research in the integration of Virtual Reality (VR) and Computer-Aide Design (CAD) has proposed a range of systems for design reviews, only a very few of them support direct modifications of original CAD data within immersive systems. Engineers, therefore, need to apply post modifications on the CAD data from a workstation to adjust the design based on discussions during the design reviews.
I argue that current distinct processes of design reviews: discussion and design adjustment should merge—so thus it could reduce the iterations, facilitate discussions and empower all users to directly apply modifications on CAD data. In this dissertation, I propose a new industrial design reviewing paradigm in which project members can adjust and compare a final design of the product within interactive systems. Considering various traits of experts involved in the review process, the interactive systems should be configurable to meet their requirements, and collaborative within or across the heterogeneous systems.
As the accessibility of native CAD data is the cornerstone for the new design review process, I first designed a back-end server, namely VR-CAD Server, which can update the CAD data with an embedded CAD engine and transmit it to the interactive systems. I implemented VR-CAD Server in a distributed network architecture that makes the system highly configurable to support heterogeneous systems and multi-user interactions between remote locations. This structure is a basis of "modifiable" project reviews, which adds a modification capability on top of the current design reviews.
Based on the distributed architecture, I explored interaction techniques for novices to modify parametric CAD data in large interactive systems. Since targeted users include non-CAD experts, interactions with the 3D-CAD model should be straightforward to learn, i.e. without the interaction on parameters, over heterogeneous systems. The choice of interactive systems differs according to the expertise and their purpose: e.g. ergonomists are likely to choose a 3D environment to assess the spatial feeling, whereas project managers might prefer discussing with a large format 2D display. I therefore designed two interaction techniques on 3D and 2D interactive systems to cover diverse reviewing scenarios, and conducted user studies for each: a Cave Automatic Virtual Environment (CAVE) system and a wall-sized display.
For the former case, I designed a 3D interaction technique on parameter modifications of the CAD data, namely ShapeGuide. With ShapeGuide, users can implicitly manipulate parametric constraints of a CAD part with a co-localized shape-based interaction. This technique prepares a set of shape variations from an original design at run-time to guide users’ hand gestures. To stabilize the gestures in 3D space, I also tested force feedback during manipulations. I performed a controlled experiment to evaluate how ShapeGuide affects a CAD data modification task in comparison to a standard one- dimensional scroll technique. Results of the experiment demonstrate that ShapeGuide is significantly faster, more efficient and preferred by the users than the scroll technique.
As for the wall-sized display, I designed ShapeCompare, an interaction, and visualization technique in which users can modify and compare multiple designs of CAD models on a large space with a touch interaction. The technique of ShapeCompare is based on ShapeGuide, which generates and presents multiple design alternatives deviated from an initial CAD model on the wall. I performed two experiments to evaluate how a large number of design alternatives displayed on a wall-sized display affects on collaborations between different experts, and how it helps their design explorations. Results of the experiments showed that with ShapeCompare, paired participants finished the collaborative reviewing task faster, preferred and found it more helpful in communications across pairs.
Lastly, I conclude with an illustration of future collaborative design review scenario across heterogeneous systems. I implemented a proof-of-concept between a CAVE system and a Wall-sized display in which both users can review and modify the CAD model in a distant location.

Ph.D. dissertations & Faculty habilitations
CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.