Path Planning of Mobile Robot Based on Improved Artificial Potential Field Method

被引:2
|
作者
Ni, Jianyun [1 ]
Du, Helei [2 ]
Wang, Tie [3 ]
Li, Hao [4 ]
Xue, Chenyang [4 ]
机构
[1] Tianjin Key Lab Control Theory & Applicat Complic, Tianjin, Peoples R China
[2] Tianjin Univ Technol, Sch Elect Engn & Automat, Tianjin, Peoples R China
[3] Tianjin Climate Ctr, Tianjin, Peoples R China
[4] Tianjin Univ Technol, Tianjin, Peoples R China
关键词
artificial potential field method; target unreachable; local minimum point; bicircular strategy; virtual target point; B-sample curve;
D O I
10.1109/CCDC58219.2023.10327324
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An improved artificial potential field method is proposed to address the problems of target unreachability and falling into local minima in the path planning process of the traditional artificial potential field method. Firstly, the distance factor between the robot and the target point is introduced to solve the target unreachability problem; secondly, the robot is guided out of the local minima point by setting the virtual target point through the double-circle strategy; finally, in order to satisfy the continuity of robot velocity and acceleration, the resulting path is smoothed by using three uniform B-sample curves. The experimental results show that the improved algorithm can effectively solve the problems of target unreachability and falling into local minima in the traditional algorithm, and the smoothness of the path after the spline treatment is better compared with the original path.
引用
收藏
页码:2058 / 2063
页数:6
相关论文
共 50 条
  • [21] Path planning of mobile robot based on artificial immune potential field algorithm
    Xu, Xin-Ying
    Xie, Jun
    Xie, Ke-Ming
    Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology, 2008, 34 (10): : 1116 - 1120
  • [22] Path Planning for Robot based on Chaotic Artificial Potential Field Method
    Zhang, Cheng
    4TH INTERNATIONAL CONFERENCE ON ADVANCED ENGINEERING AND TECHNOLOGY (4TH ICAET), 2018, 317
  • [23] A New Method for Robot Path Planning Based Artificial Potential Field
    Yang, Xing
    Yang, Wei
    Zhang, Huijuan
    Chang, Hao
    Chen, Chin-Yin
    Zhang, Shuangchi
    PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2016, : 1294 - 1299
  • [24] Path planning of mobile robot by mixing experience with modified artificial potential field method
    Min, Huasong
    Lin, Yunhan
    Wang, Sijing
    Wu, Fan
    Shen, Xia
    ADVANCES IN MECHANICAL ENGINEERING, 2015, 7 (12)
  • [25] UAV Path Planning Based on Improved Artificial Potential Field Method
    Hao, Guoqiang
    Lv, Qiang
    Huang, Zhen
    Zhao, Huanlong
    Chen, Wei
    AEROSPACE, 2023, 10 (06)
  • [26] UAV Path Planning Based on Improved Artificial Potential Field Method
    Wang, Hai
    Wang, Lei
    Gao, Xiaohua
    Yu, Xinyong
    Lu, Chen
    Wang, Xinwei
    PROCEEDINGS OF 2022 INTERNATIONAL CONFERENCE ON AUTONOMOUS UNMANNED SYSTEMS, ICAUS 2022, 2023, 1010 : 2930 - 2939
  • [27] A Flight Path Planning Method Based On Improved Artificial Potential Field
    Sun, Fanrong
    Han, Songchen
    2016 INTERNATIONAL CONFERENCE ON COMPUTER, INFORMATION AND TELECOMMUNICATION SYSTEMS (CITS), 2016, : 83 - 87
  • [28] Research on feeding path planning algorithm of bending robot based on improved artificial potential field method
    Huang, Zhuoran
    Ding, Dawei
    Xu, Shuai
    Xu, Fengyu
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 1751 - 1756
  • [29] A Hybrid Algorithm Based on Artificial Potential Field and BUG for Path Planning of Mobile Robot
    Wang, Mei
    Su, Zhiyong
    Tu, Dawei
    Lu, Xichang
    PROCEEDINGS OF 2013 2ND INTERNATIONAL CONFERENCE ON MEASUREMENT, INFORMATION AND CONTROL (ICMIC 2013), VOLS 1 & 2, 2013, : 1393 - 1398
  • [30] Improved Artificial Potential Field Method for Mobile Robots Path Planning in a Corridor Environment
    Zhang, Yuanyuan
    PROCEEDINGS OF 2022 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2022), 2022, : 185 - 190