Paper
16 December 2021 Performance evaluation of VR/MR missile virtual hoisting training
Hengwei Li, Haipin Liu, Wei Wang, Qinsheng Jiang, Qingli Wang, Chengyu Li
Author Affiliations +
Proceedings Volume 12153, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021); 121530N (2021) https://doi.org/10.1117/12.2626854
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021), 2021, Sanya, China
Abstract
Using virtual reality (VR)/mixed reality (MR) virtual hoisting training system is a low-cost and low-risk skill training method. However, the research on the performance of VR/MR virtual hoisting training is still relatively scarce. The article comprehensively evaluates the performance of VR/MR virtual hoisting training by integrating three evaluation indicators: objective performance, visual characteristics and subjective experience. The results show that the effect of the MR virtual hoisting training system is better, and the simulation reduction degree is higher. However, the VR virtual hoisting training system has good operability and is easy to master. Long-term use of the VR/MR virtual training system will cause recoverable vision loss, and there is a problem that the user's ability to actively explore the virtual environment using touch is weak. The research results have a positive effect on optimizing the allocation of training resources and improving training effectiveness.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hengwei Li, Haipin Liu, Wei Wang, Qinsheng Jiang, Qingli Wang, and Chengyu Li "Performance evaluation of VR/MR missile virtual hoisting training", Proc. SPIE 12153, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021), 121530N (16 December 2021); https://doi.org/10.1117/12.2626854
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KEYWORDS
Virtual reality

Mixed reality

Missiles

Visualization

Analytical research

Data analysis

Lithium

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