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      VR 기반 회전익 항공기 운용 절차 훈련시스템 구현 연구 = Design and Implementation of a VR-based Training System for Rotary-Wing Aircraft Operation Procedures

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      https://www.riss.kr/link?id=A110099606

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      This paper proposes a VR-based training system focused on the pre-flight inspection and engine start/stop procedures of the UH-60P rotary-wing aircraft. The system consists of a 3D virtual environment, a simulator synchronization module, multi-user collaboration, and an integrated management system. It supports real-time integration with cockpit equipment, checklist-based training, pilot–copilot collaboration, and instructor management. Trainees can systematically master operational procedures and checklists through scenario-based learning. Instructors can monitor the training process in real time and analyze performance data to provide personalized feedback and supplementary strategies based on individual error patterns and proficiency. Future research will integrate Digital Twin technology and AI-based analytics to further expand the system’s applicability to aviation training.
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      This paper proposes a VR-based training system focused on the pre-flight inspection and engine start/stop procedures of the UH-60P rotary-wing aircraft. The system consists of a 3D virtual environment, a simulator synchronization module, multi-user co...

      This paper proposes a VR-based training system focused on the pre-flight inspection and engine start/stop procedures of the UH-60P rotary-wing aircraft. The system consists of a 3D virtual environment, a simulator synchronization module, multi-user collaboration, and an integrated management system. It supports real-time integration with cockpit equipment, checklist-based training, pilot–copilot collaboration, and instructor management. Trainees can systematically master operational procedures and checklists through scenario-based learning. Instructors can monitor the training process in real time and analyze performance data to provide personalized feedback and supplementary strategies based on individual error patterns and proficiency. Future research will integrate Digital Twin technology and AI-based analytics to further expand the system’s applicability to aviation training.

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