Path Planning of Mobile Robots Based on A* Algorithm and Artificial Potential Field Algorithm

被引：0

作者：

Wang H. ^{[1
]}

Hao C. ^{[1
]}

Zhang P. ^{[1
]}

Zhang M. ^{[1
]}

Yin P. ^{[1
]}

Zhang Y. ^{[2
]}

机构：

[1] Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, 066004, Hebei

[2] National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Yanshan University, Qinhuangdao, 066004, Hebei

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2019年 / 30卷 / 20期

关键词：

A[!sup]*[!/sup] algorithm; Artificial potential field algorithm; Mobile robot; Path optimization;

D O I：

10.3969/j.issn.1004-132X.2019.20.012

中图分类号：

学科分类号：

摘要：

A hybrid algorithm was introduced based on the global and local path planning for the mobile robot navigations and collision avoidances under complex and unstructured environments. Firstly, this paper makes effective improvement on the traditional A* method. The new A* algorithm can complete the robot's path planning task. The optimized path point was obtained by using the quadratic A* search method, and the traveling path of mobile robot was shortened. Furthermore, dynamic tangential point method could effectively smooth the planned path. Secondly, considering the path and environment, the improved artificial potential field method was adopted to carry out the local path planning for the mobile robot. The problem of local minimum value was solved by adding virtual subtargets. The adaptive step size adjustment algorithm was used to dynamically optimize the step size of the mobile robot. Finally, according to different scenarios, the proposed algorithm was compared with the traditional algorithm by numerical simulation, and the results show that the proposed algorithm has some advantages in the path planning under different environments. © 2019, China Mechanical Engineering Magazine Office. All right reserved.

引用

页码：2489 / 2496

页数：7

共 25 条

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