While the A* algorithm remains the industry standard for game pathfinding, its integration into dynamic 3D environments faces trade-offs between computational performance and visual realism. This paper proposes a multi-threaded framework that enhances standard A* through Recast-based mesh generation, Bezier-curve trajectory smoothing, and density analysis for crowd coordination. We evaluate our system across ten incremental phases, from 2D mazes to complex multi-level dynamic worlds. Experimental results demonstrate that the framework maintains 350+ FPS with 1000 simultaneous agents and achieves collision-free crowd navigation through density-aware path coordination.

翻译：尽管A*算法仍是游戏寻路领域的业界标准，但其在动态三维环境中的集成始终面临计算性能与视觉真实感之间的权衡。本文提出一种多线程框架，通过基于Recast的网格生成、贝塞尔曲线轨迹平滑以及面向群体协调的密度分析，对标准A*算法进行增强。我们在从二维迷宫到复杂多层动态场景的十个渐进式测试阶段中对系统进行评估。实验结果表明：该框架在同时存在1000个智能体时仍能保持350+ FPS的帧率，并通过密度感知的路径协调实现无碰撞的群体导航。