郑州大学学报（工学版）2026，Vol.47Issue(3)：47-56,10.DOI:10.13705/j.issn.1671-6833.2025.03.018
基于改进JPS和DWA算法的移动机器人路径规划
Path Planning for Mobile Robots Based on Improved JPS and DWA Algorithms
摘要
Abstract
To tackle the problems of heightened search blindness,elevated memory usage,and redundant nodes in the output path resulting from the access of a large number of irrelevant extension nodes in traditional JPS algo-rithms,an improved JPS algorithm was proposed.This algorithm based on the priority of the target-point search di-rection and a dynamic-weight evaluation function.Firstly,according to the positions of the target point and the mo-bile robot,the priority of the direction of target point in the algorithm's path-finding process was enhanced.A dis-tance-based dynamic-weight evaluation function was introduced to mitigate the resource waste and efficiency loss caused by searching for irrelevant nodes.Meanwhile,the global path output by the improved JPS algorithm under-went secondary planning.Redundant nodes in the original path were eliminated,making the global path smoother.Secondly,the DWA algorithm was introduced and improved as a local path-planning algorithm.The improved DWA algorithm adopted a dynamic priority strategy based on collision distance to automatically avoid mobile robots on cross-paths.Finally,the improved JPS algorithm and DWA algorithm were separately simulated and verified.The results indicated that,compared with traditional jump-point algorithms,the improved algorithm in this study re-duced the average number of searched extended nodes by 60.0%,the average number of trajectory nodes by 43.6%,and the average number of path turning points by 23.9%.The improved DWA algorithm could effectively address the drawbacks and limitations of traditional DWA algorithms in dynamic environmental problems such as path conflicts,and improve the collaboration and adaptability of DWA algorithms in multi-robot path planning.关键词
跳点搜索算法/路径规划/优先级避障/动态权重评价函数/冲突路径Key words
jump point search algorithm/path planning/priority obstacle avoidance/dynamic weight evaluation function/conflict path分类
信息技术与安全科学引用本文复制引用
程博,蔡龙帅,郭桂芳,张烜..基于改进JPS和DWA算法的移动机器人路径规划[J].郑州大学学报（工学版）,2026,47(3):47-56,10.基金项目
国家自然科学基金资助项目(12102065) （12102065）
中央引导地方科技发展资金项目(XZ202301YD0003C) （XZ202301YD0003C）
西藏民族大学重大项目培育(17MDZP07) （17MDZP07）
