Mixed Reality | Evgeny Stemasov - HCI Research

pARam: Leveraging Parametric Design in Extended Reality to Support the Personalization of Artifacts for Personal Fabrication

Sun, 10 Mar 2024 09:56:15 +0100

Abstract

Extended Reality (XR) allows in-situ previewing of designs to be manufactured through Personal Fabrication (PF). These in-situ interactions exhibit advantages for PF, like incorporating the environment into the design process. However, design-for-fabrication in XR often happens through either highly complex 3D-modeling or is reduced to rudimentary adaptations of crowd-sourced models. We present pARam, a tool combining parametric designs (PDs) and XR, enabling in-situ configuration of artifacts for PF. In contrast to modeling- or search-focused approaches, pARam supports customization through embodied and practical inputs (e.g., gestures, recommendations) and evaluation (e.g., lighting estimation) without demanding complex 3D-modeling skills. We implemented pARam for HoloLens 2 and evaluated it (n=20), comparing XR and desktop conditions. Users succeeded in choosing context-related parameters and took their environment into account for their configuration using pARam. We reflect on the prospects and challenges of PDs in XR to streamline complex design methods for PF while retaining suitable expressivity.

ShapeFindAR: Exploring In-Situ Spatial Search for Physical Artifact Retrieval using Mixed Reality

Thu, 10 Mar 2022 09:56:15 +0100

Abstract

Personal fabrication is made more accessible through repositories like Thingiverse, as they replace modeling with retrieval. However, they require users to translate spatial requirements to keywords, which paints an incomplete picture of physical artifacts: proportions or morphology are non-trivially encoded through text only. We explore a vision of in-situ spatial search for (future) physical artifacts, and present ShapeFindAR, a mixed-reality tool to search for 3D models using in-situ sketches blended with textual queries. With ShapeFindAR, users search for geometry, and not necessarily precise labels, while coupling the search process to the physical environment (e.g., by sketching in-situ, extracting search terms from objects present, or tracing them). We developed ShapeFindAR for HoloLens 2, connected to a database of 3D-printable artifacts. We specify in-situ spatial search, describe its advantages, and present walkthroughs using ShapeFindAR, which highlight novel ways for users to articulate their wishes, without requiring complex modeling tools or profound domain knowledge.

Mix&Match: Towards Omitting Modelling Through In-situ Remixing of Model Repository Artifacts in Mixed Reality

Wed, 22 Apr 2020 12:00:00 +0100

Abstract

The accessibility of tools to model artifacts is one of the core driving factors for the adoption of Personal Fabrication. Subsequently, model repositories like Thingiverse became important tools in (novice) makers’ processes. They allow them to shorten or even omit the design process, offloading a majority of the effort to other parties. However, steps like measurement of surrounding constraints (e.g., clearance) which exist only inside the users’ environment, can not be similarly outsourced. We propose Mix&Match a mixed-reality-based system which allows users to browse model repositories, preview the models in-situ, and adapt them to their environment in a simple and immediate fashion. Mix&Match aims to provide users with CSG operations which can be based on both virtual and real geometry. We present interaction patterns and scenarios for Mix&Match, arguing for the combination of mixed reality and model repositories. This enables almost modeling-free personal fabrication for both novices and expert makers.