Kinematic Fuzzy Logic-Based Controller for Trajectory Tracking of Wheeled Mobile Robots in Virtual Environments

被引:0
|
作者
Perez-Juarez, Jose G. [1 ]
Garcia-Martinez, Jose R. [2 ]
Medina Santiago, Alejandro [3 ]
Cruz-Miguel, Edson E. [2 ]
Olmedo-Garcia, Luis F. [1 ]
Barra-Vazquez, Omar A. [1 ]
Rojas-Hernandez, Miguel A. [1 ]
机构
[1] Univ Veracruzana, Fac Ingn Elect & Comunicac, Lab Control & Robot, Poza Rica 93390, Mexico
[2] Univ Veracruzana, Fac Ingn Elect & Comunicac, Anal Sistemas & Tecnol Emergentes, Poza Rica 93390, Mexico
[3] Natl Inst Astrophys Opt & Elect, SECIHTI, Comp Sci Coordinat, Puebla 72840, Mexico
来源
SYMMETRY-BASEL | 2025年 / 17卷 / 02期
关键词
fuzzy controller; mobile robot; UNITY; kinematics control;
D O I
10.3390/sym17020301
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Mobile robots represent one of the most relevant areas of study within robotics due to their potential for designing and developing new nonlinear control structures that can be implemented in simulations and applications in specific environments. In this work, a fuzzy steering controller with a symmetric distribution of fuzzy numbers is proposed and designed for implementation in the kinematic model of a non-holonomic mobile robot. The symmetry in the distribution of triangular fuzzy numbers contributes to a balanced response to disturbances and minimizes systematic errors in direction estimation. Additionally, it improves the system's adaptability to various reference paths, ensuring accurate tracking and optimized performance in robot navigation. Furthermore, this fuzzy logic-based controller emulates the behavior of a classic PID controller by offering a robust and flexible alternative to traditional methods. A virtual environment was also developed using the UNITY platform to evaluate the performance of the fuzzy controller. The results were evaluated by considering the average tracking error, maximum error, steady-state error, settling time, and total distance traveled, emphasizing the trajectory error. The circular trajectory showed high accuracy with an average error of 0.0089 m, while the cross trajectory presented 0.01814 m, reflecting slight deviations in the turns. The point-to-point trajectory registered a more significant error of 0.9531 m due to abrupt transitions, although with effective corrections in a steady state. The simulation results validate the robustness of the proposed fuzzy controller, providing quantitative insights into its precision and efficiency in a virtual environment, and demonstrating the effectiveness of the proposal.
引用
收藏
页数:29
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