[1]葛文雅,李平.移动机器人全局动态路径规划融合算法[J].华侨大学学报(自然科学版),2022,43(6):809-818.[doi:10.11830/ISSN.1000-5013.202203051]
　GE Wenya,LI Ping.Global Dynamic Path Planning Fusion Algorithm for Mobile Robot[J].Journal of Huaqiao University(Natural Science),2022,43(6):809-818.[doi:10.11830/ISSN.1000-5013.202203051]
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移动机器人全局动态路径规划融合算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第43卷
期数:
2022年第6期
页码:
809-818
栏目:
出版日期:
2022-11-11

文章信息/Info

Title:
Global Dynamic Path Planning Fusion Algorithm for Mobile Robot
文章编号:
1000-5013(2022)06-0809-10
作者:
葛文雅;  李平
华侨大学 信息科学与工程学院, 福建 厦门 361021
Author(s):
GE Wenya;  LI Ping
College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China
关键词:
路径规划;  动态避障;  双速度模型;  动态窗口法;  移动机器人
Keywords:
path planning;  dynamic obstacle avoidance;  two-velocity model;  dynamic window method;  mobile robot
分类号:
TP242
DOI:
10.11830/ISSN.1000-5013.202203051
文献标志码:
A
摘要:
针对移动机器人全局动态路径规划效率较低的问题,提出一种基于安全A*算法与双速度模型动态窗口法的全局动态路径规划融合算法.首先,通过安全A*算法得到全局最优路径节点,将其作为临时目标节点,为动态规划提供全局信息,避免出现局部最优.然后,采用时间序列Bottom-Up算法减少路径节点数,从而减少迭代次数、计算代价和储存代价,提高算法效率.最后,采用双速度模型对动态窗口法进行改进,通过避障重规划机制,解决全局动态路径规划时移动机器人绕远甚至绕圈的问题,并通过MATLAB平台进行仿真实验.仿真结果表明:文中算法的规划效率可提高46.18%,保证了路径的安全性和移动机器人速度的平稳性,文中算法的路径质量和规划效率更佳.
Abstract:
Aiming at the low efficiency of global dynamic path planning of mobile robot, a global dynamic path planning fusion algorithm based on safety A* algorithm and dynamic window method with the two-velocity model is proposed. Firstly, the global optimal path node is obtained through the safety A* algorithm, which is used as the temporary target node to provide global information for dynamic planning and avoid local optimization. Then, the time series Bottom-Up algorithm is used to reduce the number of path nodes, so as to reduce the number of iterations, computational cost and storage cost, and improve the efficiency of the algorithm. Finally, the two-velocity model is used to enhance the dynamic window method, and through the obstacle avoidance and replanning mechanism to solve the problem of mobile robot going far or even in circle in global dynamic path planning, and the simulation experiment is carried out on the MATLAB platform. The simulation results show that the planning efficiency of the proposed algorithm can be improved by 46.18%, which ensures the safety of the path and the stability of the speed of the mobile robot, the path quality and planning efficiency of the proposed algorithm are better.

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备注/Memo

备注/Memo:
收稿日期: 2022-03-29
通信作者: 李平(1981-),女,副教授,博士,主要从事非线性系统与智能控制、复杂控制系统的研究.通信方式:E-mail:pingping_1213@126.com.
基金项目: 国家自然科学基金资助项目(61603144); 福建省自然科学基金资助项目(2018J01095); 福建省高校产学合作科技重大项目(2013H6016); 华侨大学中青年教师科技创新资助计划项目(ZQN-PY509)http://www.hdxb.hqu.edu.cn
更新日期/Last Update: 2022-11-20