Path Planning for Mount Robot Based on Improved Particle Swarm Optimization Algorithm

被引:3
|
作者
Li, Xudong [1 ]
Tian, Bin [1 ]
Hou, Shuaidong [1 ]
Li, Xinxin [1 ]
Li, Yang [1 ]
Liu, Chong [1 ,2 ]
Li, Jingmin [1 ,2 ,3 ]
机构
[1] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Key Lab Micro Nano Technol & Syst Liaoning Prov, Dalian 116024, Peoples R China
[3] Dalian Univ Technol, State Key Lab High Performance Precis Mfg, Dalian 116024, Peoples R China
关键词
mount robot; path planning; particle swarm optimization (PSO); adaptive strategy; PSO;
D O I
10.3390/electronics12153289
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To address the problem of cooperative work among right-angle coordinate robots in spacecraft structural plate mount tasks, an improved particle swarm optimization (PSO) algorithm was proposed to assign paths to three robots in a surface-mounted technology (SMT) machine. First, the optimization objective of path planning was established by analyzing the working process of the SMT machine. Then, the inertia weight update strategy was designed to overcome the early convergence of the traditional PSO algorithm, and the learning factor of each particle was calculated using fuzzy control to improve the global search capability. To deal with the concentration phenomenon of particles in the iterative process, the genetic algorithm (GA) was introduced when the particles were similar. The particles were divided into elite, high-quality, or low-quality particles according to their performance. New particles were generated through selection and crossover operations to maintain the particle diversity. The performance of the proposed algorithm was verified with the simulation results, which could shorten the planning path and quicken the convergence compared to the traditional PSO or GA. For large and complex maps, the proposed algorithm shortens the path by 7.49% and 11.49% compared to traditional PSO algorithms, and by 3.98% and 4.02% compared to GA.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Path Planning of Continuum Robot Based on a New Improved Particle Swarm Optimization Algorithm
    Fang Gao
    Qiang Zhao
    GuiXian Li
    [J]. Journal of Harbin Institute of Technology., 2013, 20 (04) - 84
  • [2] Path Planning of Continuum Robot Based on a New Improved Particle Swarm Optimization Algorithm
    Fang Gao
    Qiang Zhao
    Gui-Xian Li
    [J]. Journal of Harbin Institute of Technology(New series), 2013, (04) : 78 - 84
  • [3] Path Planning Based on Improved Particle Swarm Optimization Algorithm
    Jia, Huiqun
    Wei, Zhonghui
    He, Xin
    Zhang, Lei
    He, Jiawei
    Mu, Zhiya
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2018, 49 (12): : 371 - 377
  • [4] Mobile Robot Path Planning Based on Improved Particle Swarm Optimization
    Han, Yisa
    Zhang, Li
    Tan, Haiyan
    Xue, Xulu
    [J]. PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 4354 - 4358
  • [5] Global Path Planning for Mobile Robot Based on Improved Dijkstra Algorithm and Particle Swarm Optimization
    Chen, Naichao
    He, Ping
    Rui, Xianming
    [J]. ADVANCED MECHANICAL ENGINEERING, PTS 1 AND 2, 2010, 26-28 : 909 - +
  • [6] Path Planning Based on Improved Binary Particle Swarm Optimization Algorithm
    Zhang Qiaorong
    Gu Guochang
    Zhang Qiaorong
    [J]. 2008 IEEE CONFERENCE ON ROBOTICS, AUTOMATION, AND MECHATRONICS, VOLS 1 AND 2, 2008, : 470 - +
  • [7] Path Planning of Escort Robot Based on Improved Quantum Particle Swarm Optimization
    Jiao, Ming-hai
    Wei, He-xiang
    Zhang, Bo-wen
    Jin, Jia-qi
    Jia, Zhen-qiang
    Yan, Jun-lang
    [J]. PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 3730 - 3735
  • [8] Safe path planning of mobile robot based on improved particle swarm optimization
    Guo, Bingbing
    Sun, Yuan
    Chen, Yiyang
    [J]. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2024,
  • [9] Mobile Robot Path Planning Based on Improved Localized Particle Swarm Optimization
    Zhang, Lin
    Zhang, Yingjie
    Li, Yangfan
    [J]. IEEE SENSORS JOURNAL, 2021, 21 (05) : 6962 - 6972
  • [10] Global path planning for mobile robot based on improved particle swarm optimization
    Xue, Yinghua
    Tian, Guohui
    Li, Guodong
    [J]. Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2008, 36 (SUPPL. 1): : 167 - 170