[1]程博,蔡龙帅,郭桂芳,等.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(XX):1-10.[doi:10.13705/j.issn.1671-6833.2025.03.018]
　CHENG Bo,CAI Longshuai,GUO Guifang,et al.Path Planning for Mobile Robots Based on Improved JPS and DWA Algorithms[J].Journal of Zhengzhou University (Engineering Science),2026,47(XX):1-10.[doi:10.13705/j.issn.1671-6833.2025.03.018]
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基于改进 JPS 和 DWA 算法的移动机器人路径规划()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
47
期数:
2026年XX
页码:
1-10
栏目:
出版日期:
2026-09-10

文章信息/Info

Title:
Path Planning for Mobile Robots Based on Improved JPS and DWA Algorithms
作者:
程博1 ;  蔡龙帅1 ;  郭桂芳2 ;  张烜1
1. 长安大学 工程机械学院,陕西 西安 710064;2. 西藏民族大学 信息工程学院,陕西 咸阳 712082
Author(s):
CHENG Bo1 ;  CAI Longshuai1 ;  GUO Guifang2 ;  ZHANG Xuan1
1. School of Construction Machinery, Chang’ an University, Xi’an 710064, China;2. School of Information Engineering, Xizang Minzu University, Xianyang 712082, China
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
Keywords:
jump point search algorithm;  path planning;  priority obstacle avoidance;  dynamic weight evaluation function;  conflict path
分类号:
TP242
DOI:
10.13705/j.issn.1671-6833.2025.03.018
文献标志码:
A
摘要:
针对传统跳点搜索（JPS）算法在路径规划过程中，因访问大量无关扩展节点而致使搜索盲目性增强、内存占用增大，以及输出路径存在冗余节点等问题，提出了一种基于目标点搜索方向优先级和动态权重评价函数的改进JPS算法。首先，依据目标点与移动机器人的位置关系，提升算法寻路时目标点所在方向的优先级，并引入基于距离的动态权重评价函数，以此减少搜索无关节点造成的资源浪费和效率损耗。其次，对改进后的JPS算法输出的全局路径实施二次规划，消除原路径中存在的冗余节点，使全局路径更为平滑。再次，引入并改进动态窗口法（DWA）算法作为局部路径规划算法，改进后的DWA算法采用基于碰撞距离的动态优先级策略，自动避让交叉路径上的移动机器人。最后，分别对改进后的JPS算法和DWA算法进行仿真验证。结果表明：相较于传统跳点算法，所提算法搜索到的扩展节点数平均减少了60.0%，轨迹节点数平均减少了43.6%，路径拐点数平均减少了23.9%。此外，改进后的DWA算法能够有效解决传统DWA算法在处理路径冲突等动态环境问题时存在的缺陷与不足，显著提高了DWA算法在多机器人路径规划中的协同性和适应性。
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 algorithms, an improved JPS algorithm is proposed. This algorithm is based on the priority of the target-point search direction and a dynamic-weight evaluation function. Firstly, according to the positions of the target point and the mobile robot, the priority of the direction where the target point lies during the algorithm’s path-finding process is enhanced. A distance-based dynamic-weight evaluation function is 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 undergoes secondary planning. Redundant nodes in the original path are eliminated, making the global path smoother. Secondly, the DWA algorithm is introduced and improved as a local path-planning algorithm. The improved DWA algorithm adopts a dynamic priority strategy based on collision distance to automatically avoid mobile robots on cross-paths. Finally, the improved JPS algorithm and DWA algorithm are separately simulated and verified. The results indicate that, compared with traditional jump-point algorithms, the improved algorithm in this paper reduces 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 can 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.

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备注/Memo

备注/Memo:
收稿日期:2025-02-20;修订日期:2025-03-26
基金项目:中央引导地方科技发展资金项目( XZ202301YD0003C) ;国家自然科学基金资助项目( 12102065) ;西藏民族大学重大项目培育(17MDZP07)
作者简介:程博(1976— ),男,陕西大荔人,长安大学副教授,博士,主要从事智能变频控制系统研究,E-mail:2280273795@qq.com。
更新日期/Last Update: 2026-01-14