Research on Static/Dynamic Global Path Planning Based on Improved A* Algorithm for Mobile Robots

被引:1
作者
Bao, Huifang [1 ]
Fang, Jie [1 ]
Wang, Chaohai [2 ]
Li, Zebin [1 ]
Zhang, Jinsi [1 ]
Wang, Chuansheng [1 ]
机构
[1] West Anhui Univ, Sch Elect & Photoelect Engn, Luan 237012, Peoples R China
[2] Anhui Wanxiang Power Equipment Co Ltd, Luan 237012, Peoples R China
关键词
GENETIC ALGORITHM;
D O I
10.1155/2023/5098156
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In view of the problems of A* algorithm in path planning, such as collision risk, the path is not necessarily optimal, and there are numerous turning nodes. Therefore, this study proposes an improved A* algorithm to improve the quality of the planned path. First, the 8-neighborhood children of the parent node are generated, and the security of the planned path is improved by further investigating the properties of the neighbors of these children one by one to reasonably set virtual obstacles. Second, the heuristic function of A* algorithm is ameliorated to make it closer to the actual cost, so as to enhance the accuracy of the planned path; finally, the planned path is smoothed by using the cubic uniform B-spline curve to eliminate corner sharp points in the path. The simulation results show that the improved A* algorithm can not only ensure the safety and smoothness of the planned path but also obtain the shortest planned path in the static environment with different obstacle rates. In addition, we combine the improved A* algorithm with the dynamic window algorithm to enable mobile robots to realize real-time dynamic obstacle avoidance while ensuring the optimality of global path planning.
引用
收藏
页数:19
相关论文
共 39 条
  • [1] Chai H.-J., 2021, CHINESE J ELECT DEVI, V44, P362
  • [2] Chai Yeyu, 2022, Journal of Physics: Conference Series, DOI 10.1088/1742-6596/2383/1/012091
  • [3] Path Planning and Energy Efficiency of Heterogeneous Mobile Robots Using Cuckoo-Beetle Swarm Search Algorithms with Applications in UGV Obstacle Avoidance
    Chen, Dechao
    Wang, Zhixiong
    Zhou, Guanchen
    Li, Shuai
    [J]. SUSTAINABILITY, 2022, 14 (22)
  • [4] Comparison of the therapeutic effects of adipose-derived and bone marrow mesenchymal stem cells on erectile dysfunction in diabetic rats
    Chen, Sansan
    Zhu, Jianbin
    Wang, Mingzhu
    Huang, Yanting
    Qiu, Zhuolin
    Li, Jingjing
    Chen, Xinglu
    Chen, Huiying
    Xu, Mingyu
    Liu, Jun
    She, Miaoqin
    Li, Hongwei
    Yang, Xiaorong
    Wang, Yi
    Cai, Xiangsheng
    [J]. INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE, 2019, 44 (03) : 1006 - 1014
  • [5] Path Optimization Study for Vehicles Evacuation Based on Dijkstra algorithm
    Chen, Yi-zhou
    Shen, Shi-fei
    Chen, Tao
    Yang, Rui
    [J]. 2013 INTERNATIONAL CONFERENCE ON PERFORMANCE-BASED FIRE AND FIRE PROTECTION ENGINEERING (ICPFFPE 2013), 2014, 71 : 159 - 165
  • [6] Chiaravalli D., 2018, IFAC Pap, V51, P306, DOI [10.1016/j.ifacol.2018.11.559, DOI 10.1016/J.IFACOL.2018.11.559]
  • [7] Motion path planning of soccer training auxiliary robot based on genetic algorithm in fixed-point rotation environment
    Ding, Hui
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2020, 11 (12) : 6261 - 6270
  • [8] Path planning with modified A star algorithm for a mobile robot
    Duchon, Frantisek
    Babinec, Andrej
    Kajan, Martin
    Beno, Peter
    Florek, Martin
    Fico, Tomas
    Jurisica, Ladislav
    [J]. MODELLING OF MECHANICAL AND MECHATRONIC SYSTEMS, 2014, 96 : 59 - 69
  • [9] An improved A* algorithm for the industrial robot path planning with high success rate and short length
    Fu, Bing
    Chen, Lin
    Zhou, Yuntao
    Zheng, Dong
    Wei, Zhiqi
    Dai, Jun
    Pan, Haihong
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2018, 106 : 26 - 37
  • [10] Inigo-Blasco P., 2014, INT S ROBOTICS