UAV Path Planning Based on an Improved Ant Colony Algorithm

被引：5
|
作者：
Huan, Liu [1 ]
Ning, Zhang [2 ]
Qiang, Li [1 ]
机构：
[1] Natl Univ Def Technol, Coll Informat & Commun, Wuhan, Hubei, Peoples R China
[2] 95402 Army, Guiyang, Guizhou, Peoples R China
来源：
2021 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT AUTONOMOUS SYSTEMS (ICOIAS 2021) | 2021年
关键词：
UAV; path planning; ant colony algorithm; simulation;
D O I：
10.1109/ICoIAS53694.2021.00070
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to improve operational efficiency and survival probability, the optimal path of an UAV should be designed before the UAV performs a mission. The basic ant colony algorithm is easy to fall into the local optimum, and slow convergence speed. This paper improves the basic algorithm from two aspects: guidance factor and node pheromone update. The improved algorithm proposed in this paper can overcome the problems of the basic ant colony algorithm. The simulation results show that the improved ant colony algorithm is feasible for UAV path planning and the flight path optimization ability of UAV is improved.
引用
收藏
页码：357 / 360
页数：4
相关论文
共 50 条
  • [21] Dynamic Path Planning of UAV Based on Pheromone Diffusion Ant Colony Algorithm
    Zhou, Bin
    Guo, Yan
    Li, Ning
    Liu, Cunchao
    [J]. 2021 THE 7TH INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION PROCESSING, ICCIP 2021, 2021, : 16 - 21
  • [22] An improved ant colony algorithm for robot path planning
    Liu, Jianhua
    Yang, Jianguo
    Liu, Huaping
    Tian, Xingjun
    Gao, Meng
    [J]. SOFT COMPUTING, 2017, 21 (19) : 5829 - 5839
  • [23] Path Planning for Mobile Robots Based on Improved Ant Colony Algorithm
    Zhang, Jie
    Pan, Xiuqin
    [J]. COGNITIVE COMPUTING, ICCC 2022, 2022, 13734 : 3 - 13
  • [24] An improved ant colony algorithm for robot path planning
    Jianhua Liu
    Jianguo Yang
    Huaping Liu
    Xingjun Tian
    Meng Gao
    [J]. Soft Computing, 2017, 21 : 5829 - 5839
  • [25] Robot global path planning based on improved ant colony algorithm
    Wang Jinguo
    Wang Na
    Jiang Huiyu
    [J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON ADVANCED DESIGN AND MANUFACTURING ENGINEERING, 2015, 39 : 2099 - 2102
  • [26] Path planning of intelligent factory based on improved ant colony algorithm
    Hu, Man
    Cao, Jihua
    Chen, Xi
    Peng, Furong
    [J]. 2021 ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE (ACCTCS 2021), 2021, : 1 - 4
  • [27] Application of Improved Ant Colony Algorithm in Path Planning
    Li, Zhe
    Tan, Ruilian
    Ren, Baoxiang
    [J]. COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS (CISIS 2019), 2020, 993 : 596 - 603
  • [28] Robot global path planning based on improved ant colony algorithm
    Wang Rui
    Wang Jinguo
    Wang Na
    [J]. PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MATERIAL, MECHANICAL AND MANUFACTURING ENGINEERING, 2015, 27 : 946 - 949
  • [29] Picking robot path planning based on improved ant colony algorithm
    Liu, Yuke
    Zhang, Qingyong
    Yu, Lijuan
    [J]. 2019 34RD YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC), 2019, : 473 - 478
  • [30] Improved Ant Colony Algorithm for Global Path Planning
    Li, Pengfei
    Wang, Hongbo
    Li, Xiaogang
    [J]. ADVANCES IN MATERIALS, MACHINERY, ELECTRONICS I, 2017, 1820
12345