This article focuses on the poor positioning accuracy and system stability faced by virtual reality (VR) technology in virtual simulation practice, and proposes a multi-source information fusion positioning algorithm (MSF-VR). Its purpose is to enhance the user's motion restoration ability and immersion experience in a large scale environment. Based on Ultra wide Band (UWB), Inertial Measurement Unit (IMU) and Visual Simultaneity Localization and Mapping (SLAM), this study builds a state estimation model based on extended Kalman filter to achieve high-frequency and low-delay pose fusion. The system is deployed in an experimental environment of 10m×10m, and verified by the chemical experiment training scene. The experimental results show that the average positioning error of MSF-VR algorithm is controlled within 2.1cm, which is about 43% lower than that of traditional Lighthouse system, and the trajectory continuity can still be maintained during the interruption of UWB signal. The user evaluation results show that more than 85% of the participants feel that the system has significantly improved the spatial perception and learning engagement. This study proves that the fusion algorithm can effectively improve the accuracy and robustness of large-space VR system, and provide reliable technical support for virtual simulation practice.
Wang et al. (Sun,) studied this question.