2026-04-19T18:23:39Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/83692024-08-25T22:42:08Zcom_10259_4219com_10259_5086com_10259_2604col_10259_7349

Checa Cruz, David Miguel Alonso, Inés Guillén Sanz, Henar Bustillo Iglesias, Andrés Virtual reality Overhead crane Training Collaborative environments In the last decade, the rapid development and the price reduction of immersive Virtual Reality (iVR) devices allow its application to a wide range of applications. The sense of immersion and presence that these iVR devices produce surpasses any other display. These unique characteristic opens up new ways of training in Occupational Risk Prevention (ORP). iVR can create applications in collaborative training environments that mimic real situations and reinforce collaborative work and avoids unnecessary risks to the user in their training, as well as to other people or equipment that would exist if working with real equipment. Overhead cranes are one of the most interesting elements for the application of iVR training simulators. Firstly, because they are present throughout the production space and their movement involves the displacement of heavy loads that are not always well balanced. In addition, these movements occur in areas where other operators might be present and, in some cases, their collaboration is necessary during the movement stage. This research presents the design of a collaborative iVR application for training the movement of loads with overhead cranes. This developed application focuses on providing the user with the ability to proficiently operate an overhead crane. The usefulness of the iVR application was tested with 3 experienced overhead crane operators and 29 undergraduate students. These users reported that the experience was enjoyable and felt that the iVR environment was realistic and that the application would be useful to train how to handle an overhead bridge crane. 2024-01-17 2024-01-17 2022-08-26 info:eu-repo/semantics/conferenceObject 0302-9743 http://hdl.handle.net/10259/8369 10.1007/978-3-031-15546-8_10 1611-3349 eng Extended Reality. 2022, V. 13445, p. 121-129 https://doi.org/10.1007/978-3-031-15546-8_10 info:eu-repo/semantics/openAccess Springer Nature