Development and Evaluation of an AR Shooting Training System Using Hololens 2 and Reinforcement Learning

With the introduction of Defense Innovation 4.0, South Korea is actively integrating advanced technologies into military training. The current shooting training methods used by the South Korean military rely on projector-based virtual reality (VR) systems or non video see-through (NVST) head-mounted displays (HMDs), which require large spaces and lack real-world interaction. To address these limitations, this study proposes an augmented reality (AR)-based shooting training system, implementing precise tracking of firearm positions and body movements using Hololens 2 and VIVE trackers. Additionally, a reinforcement learning-based AI assistant utilizing the Proximal Policy Optimization (PPO) algorithm is introduced to analyze shooting accuracy and precision, providing real-time feedback to improve user posture. Furthermore, by adopting TCP and UDP-based socket communication, the system achieves an average latency of 2.30ms, validating its feasibility for real-time training.

Authors

Publication Details

Journal
Journal of the Korea Computer Graphics Society
Published
2025-09-01
DOI
https://doi.org/10.15701/kcgs.2025.31.4.1
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and Evaluation of an AR Shooting Training System Using Hololens 2 and Reinforcement Learning

Jung Lee, Jeonghan Kwon
Journal of the Korea Computer Graphics Society
Augmented Reality Applications
article

Development and Evaluation of an AR Shooting Training System Using Hololens 2 and Reinforcement Learning

Jung Lee, Jeonghan Kwon
article en

Abstract

With the introduction of Defense Innovation 4.0, South Korea is actively integrating advanced technologies into military training. The current shooting training methods used by the South Korean military rely on projector-based virtual reality (VR) systems or non video see-through (NVST) head-mounted displays (HMDs), which require large spaces and lack real-world interaction. To address these limitations, this study proposes an augmented reality (AR)-based shooting training system, implementing precise tracking of firearm positions and body movements using Hololens 2 and VIVE trackers. Additionally, a reinforcement learning-based AI assistant utilizing the Proximal Policy Optimization (PPO) algorithm is introduced to analyze shooting accuracy and precision, providing real-time feedback to improve user posture. Furthermore, by adopting TCP and UDP-based socket communication, the system achieves an average latency of 2.30ms, validating its feasibility for real-time training.

Journal of the Korea Computer Graphics SocietyVol. 31(4)
Openalex Percentile: Top 77%
Augmented Reality Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development and Evaluation of an AR Shooting Training System Using Hololens 2 and Reinforcement Learning — Jung Lee, Jeonghan Kwon · Journal of the Korea Computer Graphics Society (2025) | TGRS Research Map | TGRS