Research on multi-vehicle formation control based on improved artificial potential field method

被引:0
|
作者
Zhang, Hao [1 ]
Wei, Chao [1 ]
He, Yuanhao [1 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Beijing, Peoples R China
关键词
Artificial potential field method; formation coordination; four-circle model; sliding mode control; formation control; DISTRIBUTED MPC; SYSTEMS;
D O I
10.1177/09544070241265392
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Multi-vehicle formation can perform various special tasks in unstructured environment. How to take into account the safety of vehicles in avoiding obstacles and the ability to maintain formation has a certain research value. In this paper, the four-circle model of vehicle is established first, and the circle radius is adjusted according to the state of vehicle, so as to describe the safety boundary of vehicle. The improved RRT algorithm is used for the whole route planning, and the discrete path points are used as vehicle guidance. Then the artificial potential field is constructed, and the formation coordination potential field is proposed, so that the vehicles can cooperate with other vehicles to keep the preset formation as far as possible when avoiding obstacles. Then the control quantity of the vehicle is calculated according to the force condition of the vehicle in the potential field by the double exponential sliding mode control method. Finally, the effectiveness of the method is verified by the simulation experiments of triangle formation and circular formation under different working conditions, and the formation error is reduced by about 20%.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] Research on path planning of multi-rotor UAV based on improved artificial potential field method
    Liu, Zhengqing
    Wang, Xinhua
    Li, Kangyi
    2020 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE COMMUNICATION AND NETWORK SECURITY (CSCNS2020), 2021, 336
  • [22] A control scheme for improving multi-vehicle formation maneuvers
    Young, BJ
    Beard, RW
    Kelsey, JM
    PROCEEDINGS OF THE 2001 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2001, : 704 - 709
  • [23] Application of formation control for multi-vehicle robotic minesweeping
    Healey, AJ
    PROCEEDINGS OF THE 40TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5, 2001, : 1497 - 1502
  • [24] Research on Cooperative Obstacle Avoidance Control of UAV Formation Based on Improved Potential Field Method
    Dai, Jiyang
    Sun, Yijun
    Ying, Jin
    Nie, Hang
    PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 4633 - 4638
  • [25] Research on Multi-vehicle Cooperative Control Method for Autonomous Driving at Unsignalized Intersections
    Tang, Xiaolin
    Yang, Jianying
    Yang, Kai
    Li, Wenbo
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2024, 60 (20): : 217 - 228
  • [26] Collaborative Overtaking of Multi-Vehicle Systems in Dynamic Environments: A Distributed Artificial Potential Field Approach
    Xie, Songtao
    Hu, Junyan
    Ding, Zhengtao
    Arvin, Farshad
    2021 20TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), 2021, : 873 - 878
  • [27] Multi-vehicle formation control based on branch-and-bound method compatible with collision avoidance problem
    Kon, Kazuyuki
    Fukushima, Hiroaki
    Matsuno, Fumitoshi
    2007 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-9, 2007, : 3777 - 3782
  • [28] Collision avoidance method of autonomous vehicle based on improved artificial potential field algorithm
    Feng, Song
    Qian, Yubin
    Wang, Yan
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2021, 235 (14) : 3416 - 3430
  • [29] Active obstacle avoidance method of autonomous vehicle based on improved artificial potential field
    Duan, Yijian
    Yang, Changbo
    Zhu, Jihong
    Meng, Yanmei
    Liu, Xin
    International Journal of Advanced Robotic Systems, 2022, 19 (04)
  • [30] Active obstacle avoidance method of autonomous vehicle based on improved artificial potential field
    Duan, Yijian
    Yang, Changbo
    Zhu, Jihong
    Meng, Yanmei
    Liu, Xin
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2022, 19 (04):