[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(3):47-56.[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(3):47-56.[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3期
页码:
47-56
栏目:
出版日期:
2026-05-27

文章信息/Info

Title:
Path Planning for Mobile Robots Based on Improved JPS and DWA Algorithms
文章编号:
1671-6833(2026)03-0047-10
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算法将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 was proposed. This algorithm 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 of target point in the algorithm’s path-finding process was enhanced. A distance-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 underwent 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 reduced 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.

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更新日期/Last Update: 2026-05-27