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Asynchronous Manual Work in Mixed Reality Remote Collaboration

Communication avec acte
Auteur
ccMAYER, Anjela
150665 Karlsruhe Institute of Technology = Karlsruher Institut für Technologie [KIT]
469668 Institut für Informationsmanagement im Ingenieurwesen [IMI]
ccCOMBE, Theo
469668 Institut für Informationsmanagement im Ingenieurwesen [IMI]
OVTCHAROVA, Jivka
469668 Institut für Informationsmanagement im Ingenieurwesen [IMI]
150665 Karlsruhe Institute of Technology = Karlsruher Institut für Technologie [KIT]
ccCHARDONNET, Jean-Rémy
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]

URI
http://hdl.handle.net/10985/22515
DOI
10.1007/978-3-031-15553-6_2
Date
2022-08-28

Résumé

Research in Collaborative Virtual Environments (CVEs) is becoming more and more significant with increasing accessibility of Virtual Reality (VR) and Augmented Reality (AR) technology, additionally reinforced by the increasing demand for remote collaboration groupware. While the research is focusing on methods for synchronous remote collaboration, asynchronous remote collaboration remains a niche. Nevertheless, future CVEs should support both paradigms of collaborative work, since asynchronous collaboration has as well its benefits, for instance a more flexible time-coordination. In this paper we present a concept of recording and later playback of highly interactive collaborative tasks in Mixed Reality (MR). Furthermore, we apply the concept in an assembly training scenario from the manufacturing industry and test it during pilot user experiments. The pilot study compared two modalities, the first one with a manufacturing manual, and another using our concept and featuring a ghost avatar. First results revealed no significant differences between both modalities in terms of time completion, hand movements, cognitive workload and usability. Some differences were not expected, however, these results and the feedback brought by the participants provide insights to further develop our concept.

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Fin d'embargo:
2023-01-28
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Documents liés

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  • CAVE vs. HMD in Distance Perception 
    Communication avec acte
    ccCOMBE, Theo; OVTCHAROVA, Jivka; ccMERIENNE, Frédéric; ccCHARDONNET, Jean-Rémy (IEEE, 2021)
    This study aims to analyze differences between a CAVE system and a Head-Mounted Display (HMD), two technologies presenting important differences, focusing on distance perception, as past research on this factor is usually ...
  • Don't Denigrate the CAVE! A Comparative Examination of CAVE and HMD for Navigation in Virtual Worlds 
    Communication avec acte
    COMBE, Théo; ccCHARDONNET, Jean-Rémy; ccMERIENNE, Frédéric; ccOVTCHAROVA, Jivka; MESTRE, Daniel (Jean-Marie Normand and Maki Sugimoto and Veronica Sundstedt, 2023-12-06)
    This paper conducts a comprehensive analysis of user experiences by comparing navigation and cybersickness between two distinct categories of immersive devices: CAVE and HMD. Using consistent methodology and analysis for ...
  • CAVE and HMD: distance perception comparative study 
    Article dans une revue avec comité de lecture
    ccCOMBE, Theo; ccCHARDONNET, Jean-Rémy; ccMERIENNE, Frédéric; ccOVTCHAROVA, Jivka (2023-03-29)
    This paper proposes to analyse user experience using two different immersive device categories: a cave automatic virtual environment (CAVE) and a head-mounted display (HMD). While most past studies focused on one of these ...
  • Evaluating the Effectiveness of Avatar-Based Collaboration in XR for Pump Station Training Scenarios 
    Communication avec acte
    KASTNER, Kevin; MIGUEL-ALONSO, Ines; ccMAYER, Anjela; ccCHARDONNET, Jean-Rémy; ccBUSTILLO, Andres; ccOVTCHAROVA, Jivka; EISWIRTH, René; REICHWALD, Julian (IEEE, 2024-08-05)
    Immersive Virtual Reality (iVR) and Augmented Reality (AR) have become increasingly accessible tools for enhancing learning and training experiences. This study aims to evaluate the effectiveness of avatar-based collaboration ...
  • Extended Intelligence for Rapid Cognitive Reconfiguration 
    Article dans une revue avec comité de lecture
    ccMAYER, Anjela; OTTO, Simon; ccCHARDONNET, Jean-Rémy; ccPUCHTA, Alexander; ccFLEISCHER, Jürgen; ccOVTCHAROVA, Jivka (Walter de Gruyter GmbH, 2025-03-27)
    With today‘s trend toward mass customization, fast and efficient reconfiguration of manufacturing systems is essential. New artificial intelligence and robotics developments play a key role in optimizing these processes. ...

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