J
Jorge Miquel Rodriguez
Researcher at University of Navarra
Publications - 7
Citations - 573
Jorge Miquel Rodriguez is an academic researcher from University of Navarra. The author has contributed to research in topics: Virtual reality & Augmented reality. The author has an hindex of 5, co-authored 7 publications receiving 435 citations. Previous affiliations of Jorge Miquel Rodriguez include Technion – Israel Institute of Technology.
Papers
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Journal ArticleDOI
Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks
Nirit Gavish,Teresa Gutiérrez,Sabine Webel,Jorge Miquel Rodriguez,Matteo Peveri,Uli Bockholt,Franco Tecchia +6 more
TL;DR: The results suggest thatUse of the AR platform for training IMA tasks should be encouraged and use of the VR platform for that purpose should be further evaluated.
Journal ArticleDOI
Design Guidelines for the Development of Virtual Reality and Augmented Reality Training Systems for Maintenance and Assembly Tasks
TL;DR: Design guidelines for the development of Virtual Reality (VR) and Augmented Reality (AR) platforms to train technicians on maintenance and assembly tasks of industrial machineries to develop a useful mental model of the task are described.
Book ChapterDOI
Training of Procedural Tasks Through the Use of Virtual Reality and Direct Aids
Jorge Miquel Rodriguez,Teresa Gutiérrez,Emilio Jesús Lázaro Sánchez,Sara Casado,Iker Aguinaga +4 more
TL;DR: A high percentage of the human activities are based on procedural tasks, for example cooking a cake, driving a car, fixing a machine, etc and most researchers agree that procedural tasks are learnt gradually as a result of practice through repeating exposures to the task.
Journal ArticleDOI
Transfer of Skills Evaluation for Assembly and Maintenance Training
Nirit Gavish,Teresa Gutierrez Seco,Sabine Webel,Jorge Miquel Rodriguez,Matteo Peveri,Uli Bockholt +5 more
TL;DR: In this article, two different training platforms, one based on Virtual Reality (VR) and the other one on Augmented Reality (AR), were used for industrial maintenance and assembly (IMA) tasks.
Proceedings ArticleDOI
Training strategies for learning a 3D trajectory with accuracy
TL;DR: The results suggest that the best learning condition for learning a 3D trajectory with accuracy is to provide visual-haptic feedback, which facilitates the understanding of the dimension and orientation of each trajectory segment and solves any visual discrepancies that may exist.