Dynamic formation control of wheeled robots based on azimuth information
CSTR:
Author:
Affiliation:

1.School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an 710021, P. R. China;2.School of Mechanical and Electrical Engineering, Shaanxi University of Science & Technology, Xi’an 710021, P. R. China

Clc Number:

TP242

Fund Project:

Supported by Key Research and Development Program of Shaanxi Province(2023-YBGY-277,2023-YBGY-409).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Addressing the scenario in which each robot can only acquire the azimuth information of adjacent robots in dynamic formations with incomplete constraints, this paper proposes a distributed PID formation control algorithm based solely on azimuth information. With considering that the pilot robot is susceptible to disturbances such as wind direction or road surface irregularities, which may disrupt formation maintenance, the algorithm introduces relative position and velocity feedback of the follower robots. This approach effectively eliminates steady-state error, suppresses the influence of disturbances, improves system dynamic performance, and ensures global system stability. Then, the Routh-Hurwitz stability criterion is used for stability analysis, verifying the global stability of the formation system. Finally, simulation experiments compare the performance of the proposed control law with control laws based on pure proportional and proportional-integral strategies in terms of convergence speed and disturbance rejection. The results show that the proposed control law enables the formation to recover after disturbances and achieve rapid trajectory tracking of the leader, with the relative maximum deviation of the total azimuth error reduced by 5.4%.

    Reference
    Related
    Cited by
Get Citation

李艳,贺彬彬,李明辉,戴庆瑜.基于方位信息的轮式机器人动态编队控制[J].重庆大学学报,2025,48(4):84~96

Copy
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:July 22,2023
  • Revised:
  • Adopted:
  • Online: April 25,2025
  • Published:
Article QR Code