Virtual reality for immersive multi-user firefighter-training scenarios

作     者：Philipp BRAUN Michaela GRAFELMANN Felix GILL Hauke STOLZ Johannes HINCKELDEYN Ann-Kathrin LANGE 

作者机构：Hamburg University of TechnologyHamburg 21073Germany 

出 版 物：《Virtual Reality & Intelligent Hardware》 (虚拟现实与智能硬件（中英文）)

年 卷 期：2022年第4卷第5期

页      面：406-417页

核心收录：

学科分类：03[法学] 08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0306[法学-公安学] 

基　　金：Supported by Authority for Science  Research and Equality of the Free and Hanseatic City of Hamburg。 

主　　题：Virtual reality Multi-user Motion capture Training Firefighting 

摘      要：Background Virtual reality(VR)applications can be used to provide comprehensive training scenarios that are difficult or impossible to represent in physical configurations.This includes team training for emergency services such as firefighting.Creating a high level of immersion is essential for achieving effective virtual training.In this respect,motion-capture systems offer the possibility of creating highly immersive multi-user training experiences,including full-body avatars.Methods This study presents a preliminary prototype that helps extin-guish a virtual fire on a container ship as a VR training scenario.The prototype provides a full-body and multi-user VR experience based on the synthesis of position data provided by the motion-capture system and orientation data from the VR headsets.Moreover,the prototype facilitates an initial evaluation of the results.Results The results confirm the value of using VR for training procedures that are difficult to implement in the real world.Furthermore,the results show that motion-capture-based VR technologies are particularly useful for firefighting training,in which participants can collaborate in difficult-to-access environments.However,this study also indicates that increasing the immersion in such training remains a challenge.Conclusions This study presents a prototypical VR application that enables the multi-user training of maritime firefighters.Future research should evaluate the initial results,provide more extensive training scenarios,and measure the training progress.