Improving VR Welding Simulator Tracking Accuracy Through IMU-SLAM Fusion

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Publicado en:Electronics vol. 14, no. 23 (2025), p. 4693-4721
Autor principal: Kwang-Seong, Shin
Otros Autores: Kim Jong Chan, Cho, Kyung Won, Cho, Won Ik
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MDPI AG
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024 7 |a 10.3390/electronics14234693  |2 doi 
035 |a 3280947223 
045 2 |b d20250101  |b d20251231 
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100 1 |a Kwang-Seong, Shin  |u Department of Computer Engineering, Sunchon National University, Suncheon 57992, Republic of Korea; waver@scnu.ac.kr (K.-S.S.); seaghost@scnu.ac.kr (J.C.K.) 
245 1 |a Improving VR Welding Simulator Tracking Accuracy Through IMU-SLAM Fusion 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Virtual reality (VR) welding simulators provide safe and cost-effective training environments, but precise torch tracking remains a key challenge. Current commercial systems are limited in accurate bead simulation and posture feedback due to tracking errors of 3–10 mm, while external motion capture systems offer high precision but suffer from high cost and installation complexity issues. Therefore, a new approach is needed that achieves high precision while maintaining cost efficiency. This paper proposes an IMU-SLAM fusion-based tracking algorithm. The method combines Inertial Measurement Unit (IMU) data with visual–inertial SLAM (Simultaneous Localization and Mapping) for sensor fusion and applies a drift correction technique utilizing the periodic weaving patterns of the welding torch. This achieves precision below 5 mm without requiring external equipment. Experimental results demonstrate an average 3.8 mm RMSE (Root Mean Square Error) across 15 datasets spanning three welding scenarios, showing a 1.8× accuracy improvement over commercial baselines. Results were validated against OptiTrack ground truth data. Latency was maintained below 100 ms to meet real-time haptic feedback requirements, ensuring responsive interaction during training sessions. The proposed approach is a software solution using only standard VR hardware, eliminating the need for expensive external tracking equipment installation. User studies confirmed significant improvements in tracking quality perception from 6.8 to 8.4/10 and bead simulation realism from 7.1 to 8.7/10, demonstrating the practical effectiveness of the proposed method. 
653 |a Simultaneous localization and mapping 
653 |a Simulators 
653 |a Motion capture 
653 |a Accuracy 
653 |a Collaboration 
653 |a Deep learning 
653 |a Feedback 
653 |a Optimization 
653 |a Tracking errors 
653 |a Virtual reality 
653 |a Global positioning systems--GPS 
653 |a Velocity 
653 |a Cameras 
653 |a Graphs 
653 |a Tracking devices 
653 |a Costs 
653 |a Root-mean-square errors 
653 |a Ground truth 
653 |a Sensors 
653 |a Effectiveness 
653 |a Inertial platforms 
653 |a Real time 
653 |a Welding 
700 1 |a Kim Jong Chan  |u Department of Computer Engineering, Sunchon National University, Suncheon 57992, Republic of Korea; waver@scnu.ac.kr (K.-S.S.); seaghost@scnu.ac.kr (J.C.K.) 
700 1 |a Cho, Kyung Won  |u Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore 639798, Singapore 
700 1 |a Cho, Won Ik  |u School of Mechanical and Aerospace Engineering, Sunchon National University, Suncheon 57992, Republic of Korea 
773 0 |t Electronics  |g vol. 14, no. 23 (2025), p. 4693-4721 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3280947223/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3280947223/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3280947223/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch