Year: 2025
Type: article
Abstract: 针对跳点搜索(Jump Point Search, JPS)算法搜索方向不明确、搜索范围过大和存在冗余节点等问题，提出一种改进JPS算法。首先，对启发式函数添加权重系数提升搜索效率；其次，设置椭圆形动态扩展边界限制搜索范围；最后，通过提取关键跳点优化拐点数量和路径长度。实验结果表明，改进算法与传统算法相比，拐点和计算节点数更少，路径长度更短，搜索效率更高。To address the issues of unclear search direction, excessive search range, and redundant nodes in the Jump Point Search (JPS) algorithm, an improved JPS algorithm is proposed. Firstly, a weight coefficient is added to the heuristic function to enhance search efficiency. Secondly, an elliptical dynamic expansion boundary is established to limit the search range. Finally, key jump points are extracted to optimize the number of inflection points and path length. Experimental results demonstrate that compared with traditional algorithms, the improved algorithm achieves fewer inflection points and computational nodes, shorter path length, and higher search efficiency.
Author: 伟博 孙
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4412648682