Loading...

Trajectory control of autonomous mobile robots considering disturbance with machine learning agents

Tahmasbi, M ; Sharif University of Technology | 2023

0 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/s40430-023-04187-w
  3. Publisher: Springer Science and Business Media Deutschland GmbH , 2023
  4. Abstract:
  5. Mobile robots as automatic machines have the capability to move around various environments and have considered because of wide range of applications in the industrial settings. It is vital for a mobile robot to determine its errors in indeterminate conditions and provide a robust and high performance controller along with trajectory control. Hence, the research has attempted to give a learning-based controller method for wheeled mobile robots in the presence of disturbance. The proposed method, use LQR controller and the Bat algorithm based on machine learning agents to calculate and identify control errors and satisfy the stability. The wheeled mobile robot should track the reference path in the mode by observing and estimating errors. Compared to other presented methods, the control of wheeled mobile robots has been investigated in the presence of noise and unmodeled dynamic. The proposed algorithm is simulated in MATLAB software as virtual environment. The obtained results are compared with a classical method and is illustrated that the discussed method has reasonable performance compared to the classical method. © 2023, The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering
  6. Keywords:
  7. Autonomous mobile robots ; Bat algorithm ; LQR controller ; Machine learning ; Trajectory control
  8. Source: Journal of the Brazilian Society of Mechanical Sciences and Engineering ; Volume 45, Issue 6 , 2023 ; 16785878 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s40430-023-04187-w