scholarly journals Development and assessment of a tractor driving simulator with immersive virtual reality for training to avoid occupational hazards

2017 ◽  
Vol 143 ◽  
pp. 111-118 ◽  
Author(s):  
D. Ojados Gonzalez ◽  
B. Martin-Gorriz ◽  
I. Ibarra Berrocal ◽  
A. Macian Morales ◽  
G. Adolfo Salcedo ◽  
...  
10.6036/10241 ◽  
2021 ◽  
Vol 96 (6) ◽  
pp. 620-626
Author(s):  
DAVID CHECA CRUZ ◽  
KIM MARTINEZ ◽  
ROQUE ALFREDO OSORNIO RIOS ◽  
ANDRÉS BUSTILLO

This work discuss the possibilities of Immersive Virtual Reality (iVR) environments in occupational risk prevention in the manufacturing industry. Firstly, a framework for iVR experiences design is presented. Secondly, two examples to demonstrate the usefulness of this scheme for the detection of occupational hazards are discussed. In the first one, the worker controls an overhead crane in a realistic iVR environment. Realism is searched to intensify user´s presence in the iVR and, therefore, learning effectiveness. Visual quality is maximized and natural movements and load´s inertias are programmed with this objective. The user performs different critical operations in this application. The tasks becomes more complex while the user gets used to the iVR serious game: noise level, bad lighting, presence of other workers in the working area and, especially, load unbalance. Under these conditions, the user must carry out different common tasks while avoiding accidents. In the second one, the worker moves through a factory and identifies different risk situations, taking the corresponding corrective measures. While in the first application, the user interacts with the virtual environment using a real overhead crane keypad to increase his immersion, in the second one a standard iVR interface is used, because it simulates in a natural way the interaction with virtual objects. In both cases, a data acquisition system, including positioning and eyetracking, allows the trainer to directly provide feedback to the user on his performance. Keywords: Virtual Reality; Occupational Risk Prevention; Industry 4.0; Overhead crane; Educational Games


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 48952-48962
Author(s):  
Bruno Peixoto ◽  
Rafael Pinto ◽  
Miguel Melo ◽  
Luciana Cabral ◽  
Maximino Bessa

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 26
Author(s):  
David González-Ortega ◽  
Francisco Javier Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.


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