[1]李登峰,杨 曦.基于改进智能水滴算法的移动机器人路径规划[J].计算机技术与发展,2019,29(12):49-54.[doi:10. 3969 / j. issn. 1673-629X. 2019. 12. 009]
　LI Deng-feng,YANG Xi.Path Planning of Mobile Robot Based on Improved Intelligent Water Drop Algorithm[J].,2019,29(12):49-54.[doi:10. 3969 / j. issn. 1673-629X. 2019. 12. 009]
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基于改进智能水滴算法的移动机器人路径规划()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年12期
页码:
49-54
栏目:
智能、算法、系统工程
出版日期:
2019-12-10

文章信息/Info

Title:
Path Planning of Mobile Robot Based on Improved Intelligent Water Drop Algorithm
文章编号:
1673-629X(2019)12-0049-06
作者:
李登峰; 杨 曦
长安大学 电子与控制工程学院,陕西 西安 710064
Author(s):
LI Deng-feng; YANG Xi
School of Electrical and Control Engineering,Chang’an University,Xi’an 710064,China
关键词:
智能水滴算法; 移动机器人; 路径规划; 栅格模型; 优化算法
Keywords:
intelligent water drop algorithm; mobile robot; path planning; grid model; optimization algorithm
分类号:
TP391;TP18
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 12. 009
摘要:
为提高移动机器人路径规划算法的精度,提出一种基于改进智能水滴算法的移动机器人路径规划算法。 首先,以跑步机运动模型中仿人机器人的运行为对象,对其模型进行研究,然后利用栅格模型对移动机器人运行区域及行进方向进行模型构建,得到机器人行进的 8 个方向模型,同时对移动机器人路径规划问题进行建模,得到移动机器人的相应约束优化问题模型;其次,介绍智能水滴算法,并将其引入路径规划模型进行模型优化,随后,采用邻域扰动策略对智能水滴进化过程进行优化改进,增加了路径规划成功率,实现了算法性能的进一步提升;最后,进行了标准测试函数以及机器人路径规划算例上的实验仿真,结果表明该算法提高了收敛速度和精度,优化了移动机器人路径规划结果。
Abstract:
To improve the accuracy of path planning algorithm for mobile robots,a path planning algorithm for mobile robots based on improved intelligent water drop algorithm is proposed. Firstly,the running model of the robot in the treadmill motion model is taken as the object to be studied,and then the grid model is used to model the running region and the traveling direction of the mobile robot to obtain eight moving direction model of the robot. At the same time,the mobile robot path planning is modeled and the corresponding constrained optimization problem model is given. Secondly,the intelligent water droplets algorithm is introduced into the path planning model for model optimization,and the neighborhood perturbation strategy is used to optimize and improve the intelligent water droplets evolution process. The path planning success rate is increased,which further improves the performance of the algorithm. Finally,the simulation of standard test function and the robot path planning example is carried out,which shows that this algorithm improves the convergence speed and precision and optimizes the path planning of mobile robot.

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更新日期/Last Update: 2019-12-10