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<p>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&#xa0;s to 0.50&#xa0;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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月24日

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  • Yanyan Lu

摘要

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.