Safe path planning of mobile robot based on improved particle swarm optimization

被引:1
|
作者
Guo, Bingbing [1 ]
Sun, Yuan [1 ]
Chen, Yiyang [1 ]
机构
[1] Soochow Univ, Sch Mech & Elect Engn, Suzhou 215131, Peoples R China
基金
中国国家自然科学基金;
关键词
Path planning; control barrier function; particle swarm optimization; obstacle avoidance; AUTONOMOUS NAVIGATION; MODEL;
D O I
10.1177/01423312241264860
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Path planning is a fundamental aspect of mobile robot navigation, playing a crucial role in enabling robots to autonomously navigate while avoiding obstacles. Nevertheless, traditional path planning algorithms face navigation challenges, including obstacle avoidance and the potential for getting stuck in local minima or deadlocks along the path. To tackle these challenges, the study proposes an enhanced path planning method based on control barrier function (CBF). This approach introduces a safety velocity adjustment mechanism based on CBF and combines it with the particle swarm optimization (PSO), adjusting the safe speed in global planning and addressing the issue of local minima. Experimental simulations are conducted to validate the flexibility and global optimization performance of the proposed path planning method across various obstacle scenarios.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Path Planning of Continuum Robot Based on a New Improved Particle Swarm Optimization Algorithm
    Fang Gao
    Qiang Zhao
    GuiXian Li
    Journal of Harbin Institute of Technology, 2013, 20 (04) : 78 - 84
  • [22] Research on Autonomous Moving Robot Path Planning Based on Improved Particle Swarm Optimization
    Nie, Zhibin
    Yang, Xiaobing
    Gao, Shihong
    Zheng, Yan
    Wang, Jianhui
    Wang, Zhanshan
    2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2016, : 2532 - 2536
  • [23] Obstacle Avoidance Path Planning of Space Robot Based on Improved Particle Swarm Optimization
    Zhang, Jianxia
    Zhang, Jianxin
    Zhang, Qiang
    Wei, Xiaopeng
    SYMMETRY-BASEL, 2022, 14 (05):
  • [24] Path Planning of Continuum Robot Based on a New Improved Particle Swarm Optimization Algorithm
    Fang Gao
    Qiang Zhao
    Gui-Xian Li
    Journal of Harbin Institute of Technology(New series), 2013, (04) : 78 - 84
  • [25] Mobile Node Path Planning Based on Particle Swarm Optimization
    Chen Chuixin
    Cheng Hanxiang
    2019 IEEE 11TH INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2019), 2019, : 22 - 26
  • [26] Path planning for mobile robot using the particle swarm optimization with mutation operator
    Qin, YQ
    Sun, DA
    Li, N
    Cen, YG
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 2473 - 2478
  • [27] Smooth path planning of a mobile robot using stochastic particle swarm optimization
    Chen, Xin
    Li, Yangmin
    IEEE ICMA 2006: PROCEEDING OF THE 2006 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-3, PROCEEDINGS, 2006, : 1722 - +
  • [28] A Robust Path Planning For Mobile Robot Using Smart Particle Swarm Optimization
    Dewang, Harshal S.
    Mohanty, Prases K.
    Kundu, Shubhasri
    INTERNATIONAL CONFERENCE ON ROBOTICS AND SMART MANUFACTURING (ROSMA2018), 2018, 133 : 290 - 297
  • [29] Path Planning Based on Improved Particle Swarm Optimization Algorithm
    Jia H.
    Wei Z.
    He X.
    Zhang L.
    He J.
    Mu Z.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2018, 49 (12): : 371 - 377
  • [30] Ship Path Planning Based on Improved Particle Swarm Optimization
    Liu Yujie
    Pan Yu
    Su Yixin
    Zhang Huajun
    Zhang Danhong
    Song Yong
    2018 CHINESE AUTOMATION CONGRESS (CAC), 2018, : 226 - 230