Year: 2025
Type: article
Abstract: 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.
Source: Electronics
Authors: Kwang-Seong Shin, Jong Chan Kim, Kyung Won Cho, Won Ik Cho
Institutions: Sunchon National University, Nanyang Technological University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: Sunchon National University
OpenAlex ID: W4416787564