Research on Operation Training of Large Vehicle Based on Augmented Reality Technology
- DOI
- 10.2991/978-94-6463-172-2_28How to use a DOI?
- Keywords
- Augmented Reality; Training of Large Vehicle; Operation
- Abstract
With the continuous development of new technologies such as virtual reality, augmented reality and mixed reality, its application in the field of large vehicle operation training is becoming more and more extensive. Based on the practice of smoking vehicle operation and training, this paper designs an intelligent interactive training system based on the integration of artificial intelligence technology and augmented reality technology, and researches and demonstrates the key technologies of its implementation. It realizes the superposition and interaction of virtual equipment, such as virtual animation and model, and real installation and real scene, provides a good virtual interactive experience of augmented reality, meets the training needs under complex conditions in the field, and provides technical support for the improvement of training quality and benefit.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ming Wu AU - Gang An AU - Wenxuan Sun AU - Wei Li AU - Luoguo Wang PY - 2023 DA - 2023/06/30 TI - Research on Operation Training of Large Vehicle Based on Augmented Reality Technology BT - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023) PB - Atlantis Press SP - 254 EP - 264 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-172-2_28 DO - 10.2991/978-94-6463-172-2_28 ID - Wu2023 ER -