【摘要】 为改善传统路径规划A~*算法搜索速度慢的问题，提出了一种基于双向搜索改进A~*算法。新型算法选用欧几里得距离作为启发式函数并引入双向搜索策略，采用了24邻域搜索法和自适应地图的动态权重系数实现对启发式函数的自动调节，提高算法的路径规划效率及其对不同地图的适应性。在不同环境下的进行了两组仿真实验，结果表明，与现有4种算法比较，该算法在搜索节点数量和规划时间方面具有较大的性能提升。更多还原

【Abstract】 In order to address the issue of slow search speed in the traditional A~* algorithm for path planning, a novel approach based on bidirectional search, known as the improved A~* algorithm, is proposed. This new algorithm utilizes the Euclidean distance as the heuristic function and incorporates bidirectional search strategy. Additionally, it employs a 24-neighborhood search method and dynamically adjusts the weight coefficients of the heuristic function using an adaptive map, thereby enhancing the efficiency of path planning and adapting to different maps. Two sets of simulation experiments were conducted in different environments. Results demonstrate significant performance improvements of the algorithm in terms of the number of search nodes and planning time, as compared with the four existing algorithms.更多还原