1
Mechanical Engineering Department, Islamic Azad University, Karaj Branch, Iran
2
School of Mechanical Engineering, College of Engineering, University of Tehran, Iran
Abstract
Solution to the safe and collision-free trajectory of the wheeled mobile robot in cluttered environments containing the static and/or dynamic obstacle has become a very popular and challenging research topic in the last decade. Notwithstanding of the amount of publications dealing with the different aspects of this field, the ongoing efforts to address the more effective and creative methods is continued. In this article, the effectiveness of the real-time harmonic potential field theory based on the panel method to generate the reference path and the orientation of the trajectory tracking control of the three-wheel nonholonomic robot in the presence of variable-size dynamic obstacle is investigated. The hybrid control strategy based on a backstepping kinematic and regressor-based adaptive integral sliding mode dynamic control in the presence of disturbance in the torque level and parameter uncertainties is employed. In order to illustrate the performance of the proposed adaptive algorithm, a hybrid conventional integral sliding mode dynamic control has been established. The employed control methods ensure the stability of the controlled system according to Lyapunov’s stability law. The results of simulation program show the remarkable performance of the both methods as the robust dynamic control of the mobile robot in tracking the reference path in unstructured environment containing variable-size dynamic obstacle with outstanding disturbance suppression characteristic.
Nikranjbar, A., Haidari, M., Atai, A. (2018). Adaptive Sliding Mode Tracking Control of Mobile Robot in Dynamic Environment Using Artificial Potential Fields. Journal of Computer & Robotics, 11(1), 1-14.
MLA
Abolfath Nikranjbar; Masoud Haidari; Ali Asghar Atai. "Adaptive Sliding Mode Tracking Control of Mobile Robot in Dynamic Environment Using Artificial Potential Fields". Journal of Computer & Robotics, 11, 1, 2018, 1-14.
HARVARD
Nikranjbar, A., Haidari, M., Atai, A. (2018). 'Adaptive Sliding Mode Tracking Control of Mobile Robot in Dynamic Environment Using Artificial Potential Fields', Journal of Computer & Robotics, 11(1), pp. 1-14.
VANCOUVER
Nikranjbar, A., Haidari, M., Atai, A. Adaptive Sliding Mode Tracking Control of Mobile Robot in Dynamic Environment Using Artificial Potential Fields. Journal of Computer & Robotics, 2018; 11(1): 1-14.
)