Construction of UE4 model and virtual experience technology for Qiang ethnic architectural environment based on improved A* algorithm

With the acceleration of modernization, the traditional architecture of the Qiang ethnic group is facing challenges in terms of protection and inheritance. To better showcase the architectural culture of the Qiang ethnic group and enhance its experience in virtual environments, this study adopts adaptive strategies to optimize the traditional A* algorithm. It introduces reverse optimization strategies and reward value diffusion strategies, and further optimizes the efficiency of path planning. By combining Unreal Engine 4 (UE4) model construction technology, high-precision modeling, and rendering of the Qiang ethnic architectural environment have been achieved. In terms of interaction response time, the mean response time of the improved A* was 0.35 s to 0.50 s, significantly lower than other algorithms. In terms of navigation ability, the navigation accuracy was as high as 95.3% and 96.3%, with the smallest navigation error. Meanwhile, the improved A* had the shortest rendering time and the lowest memory usage. This indicates that the improved A* algorithm can quickly respond to user operation requests, reduce waiting time, and significantly enhance user engagement and interest, thereby increasing user immersion. This study provides strong technical support for the virtual display and cultural inheritance of the Qiang ethnic architectural environment.

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Publication Details

Journal
Scientific Reports
Published
2025-11-24
DOI
https://doi.org/10.1038/s41598-025-25617-w
Primary Topic
Advanced Technology in Applications
Type
article
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article

Construction of UE4 model and virtual experience technology for Qiang ethnic architectural environment based on improved A* algorithm

Yan-Yan Lu
Scientific Reports
Advanced Technology in Applications
article

Construction of UE4 model and virtual experience technology for Qiang ethnic architectural environment based on improved A* algorithm

Yan-Yan Lu
article en

Abstract

With the acceleration of modernization, the traditional architecture of the Qiang ethnic group is facing challenges in terms of protection and inheritance. To better showcase the architectural culture of the Qiang ethnic group and enhance its experience in virtual environments, this study adopts adaptive strategies to optimize the traditional A* algorithm. It introduces reverse optimization strategies and reward value diffusion strategies, and further optimizes the efficiency of path planning. By combining Unreal Engine 4 (UE4) model construction technology, high-precision modeling, and rendering of the Qiang ethnic architectural environment have been achieved. In terms of interaction response time, the mean response time of the improved A* was 0.35 s to 0.50 s, significantly lower than other algorithms. In terms of navigation ability, the navigation accuracy was as high as 95.3% and 96.3%, with the smallest navigation error. Meanwhile, the improved A* had the shortest rendering time and the lowest memory usage. This indicates that the improved A* algorithm can quickly respond to user operation requests, reduce waiting time, and significantly enhance user engagement and interest, thereby increasing user immersion. This study provides strong technical support for the virtual display and cultural inheritance of the Qiang ethnic architectural environment.

Scientific ReportsVol. 15(1)
Nanjing University of the Arts (CN), Nanjing University (CN)
Openalex Percentile: Top 51%
Advanced Technology in Applications
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Construction of UE4 model and virtual experience technology for Qiang ethnic architectural environment based on improved A* algorithm — Yan-Yan Lu · Scientific Reports (2025) | TGRS Research Map | TGRS