K
Katharina Mura
Researcher at German Research Centre for Artificial Intelligence
Publications - 9
Citations - 510
Katharina Mura is an academic researcher from German Research Centre for Artificial Intelligence. The author has contributed to research in topics: Virtual training & Augmented reality. The author has an hindex of 7, co-authored 9 publications receiving 415 citations.
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Innovative system for real-time ergonomic feedback in industrial manufacturing.
TL;DR: Results demonstrate that the real-time ergonomic feedback significantly decreased the outcome of both globally as well as locally hazardous RULA values that are associated with increased risk for musculoskeletal disorders.
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Introduction and establishment of virtual training in the factory of the future
TL;DR: The design, implementation and evaluation of an advanced virtual training system, which has been developed in the EU-FP7 project VISTRA, is introduced, which is one of the leading industries in adopting future factory concepts and technologies such as cyber-physical systems and internet of things.
Journal ArticleDOI
Establishing the Usability of a Virtual Training System for Assembly Operations within the Automotive Industry
Alyson Langley,Glyn Lawson,Setia Hermawati,Mirabelle D'Cruz,Judith Apold,Frank Arlt,Katharina Mura +6 more
TL;DR: In this article, the authors investigated the effectiveness and efficiency of the first prototype of the virtual training system VTS developed within the VISTRA Virtual Simulation and Training of Assembly and Service Processes in Digital Factories project FP7-ICT-285176, using real end users from the OPEL automotive plant in Russelsheim, Germany.
Journal ArticleDOI
Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks
Gabriele Bleser,Dima Damen,Ardhendu Behera,Gustaf Hendeby,Katharina Mura,Markus Miezal,Andrew P. Gee,Nils Petersen,Gustavo Maçães,Hugo Domingues,Dominic Gorecky,Luis Almeida,Walterio W. Mayol-Cuevas,Andrew Calway,Anthony G. Cohn,David C. Hogg,Didier Stricker +16 more
TL;DR: A scalable concept and an integrated system demonstrator designed for the transfer of learnt workflows from observing multiple expert operators and then transfer the learnt workflow models to novice users are presented.
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IBES: a tool for creating instructions based on event segmentation.
TL;DR: IBES, a tool with which users can quickly and easily create multimedia, step-by-step instructions by segmenting a video of a task into segments, is described and suggestions for research on user-oriented instructional design based on this tool are given.