Research on Improved Potential Field Ant Colony Algorithm for UAV Path Planning

被引：4
作者：
Chen, Tao [1 ]
Lv, Xinyu [1 ]
Wang, Shengying [1 ]
Ta, Na [1 ]
Zhao, Jing [2 ]
Chen, Xinpei [3 ]
Xiao, Mingxia [1 ]
Wei, Haicheng [1 ]
机构：
[1] North Minzu Univ, Sch Elect & Informat Engn, Yinchuan 750021, Ningxia, Peoples R China
[2] Ningxia Univ, Sch Informat Engn, Yinchuan 750021, Ningxia, Peoples R China
[3] Ningxia Presch Educ Coll, Educ Informat Ctr, Yinchuan 750001, Ningxia, Peoples R China
来源：
PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年
基金：
中国国家自然科学基金;
关键词：
path planning; ant colony algorithm; artificial potential field algorithm; the decrease coefficient of potential field resultant force;
D O I：
10.1109/CCDC52312.2021.9602445
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 solve the problems of slow convergence speed and prone to local optimization in ant colony algorithm, an improved ant colony algorithm of potential field is proposed in this study. Firstly, the method of pheromone affected by artificial potential field is introduced to reduce the blindness of the ant colony. Then, the potential field heuristic information is used to accelerate the convergence speed of ant colony algorithm. Finally, the decrease coefficient of potential field resultant force is used to solve the local optimal problem. Compare with the traditional algorithm, the experiments show that the improved algorithm in this paper can get better results, in terms of path length and the number of convergence iterations, the average search time for convergence is reduced by 44.83% in the 20x20 map.
引用
收藏
页码：535 / 539
页数：5
相关论文
共 50 条
  • [31] Path planning with multi-factor improved ant colony algorithm
    Yang L.
    Fu L.
    Guo N.
    Yang Z.
    Guo H.
    Xu X.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2023, 29 (08): : 2537 - 2549
  • [32] Application of improved ant colony algorithm in mobile robot path planning
    Gao, Xiang
    Jin, Wuyin
    Zhang, Xia
    Zhang, Binfei
    2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, AND INTELLIGENT COMPUTING (CAMMIC 2022), 2022, 12259
  • [33] Path Planning for Mobile Robots Based on Improved Ant Colony Algorithm
    Zhang, Jie
    Pan, Xiuqin
    COGNITIVE COMPUTING, ICCC 2022, 2022, 13734 : 3 - 13
  • [34] Improved design of ant colony algorithm and its application in path planning
    Li X.
    Ma R.
    Zhang S.
    Hou Y.
    Pei Y.
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2020, 41
  • [35] The Application of an Improved Ant Colony Algorithm in Mobile Robot Path Planning
    Zhu Xiaoguang
    Han Qingyao
    Wang Zhangqi
    MATERIALS, MECHATRONICS AND AUTOMATION, PTS 1-3, 2011, 467-469 : 222 - 225
  • [36] Path planning of mobile robot based on improved ant colony algorithm
    Lu Kai-feng
    Peng Li
    Proceedings of the 2007 Chinese Control and Decision Conference, 2007, : 526 - +
  • [37] Research on ship collision avoidance path planning based on modified potential field ant colony algorithm
    Gao, Pan
    Zhou, Li
    Zhao, Xu
    Shao, Bo
    OCEAN & COASTAL MANAGEMENT, 2023, 235
  • [38] Mobile Robot Path Planning Based on Improved Ant Colony Algorithm
    Su, Qinggang
    Yu, Wangwang
    Liu, Jun
    2021 ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE (ACCTCS 2021), 2021, : 220 - 224
  • [39] Research on Path Planning for Humanoid Robot based on Ant Colony Algorithm
    Zhang Xiaoliang
    Zhong Qiubo
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND SERVICE SYSTEM (CSSS), 2014, 109 : 310 - 313
  • [40] An Improved Ant Colony Algorithm Of Three dimensional Path Planning
    Qian, Weijie
    Zhou, Lanfeng
    Yang, Lina
    Xu, Wei
    2017 10TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL. 1, 2017, : 119 - 122
12345