Neural Network-Based TID Controller for Wheeled Mobile Robot Trajectory Tracking

2021 ◽  
pp. 207-215
Author(s):  
Najva Hassan ◽  
Abdul Saleem
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Trajectory Tracking ◽  
Wheeled Mobile Robot ◽  
Robot Trajectory

NEURAL NETWORK PREDICTIVE TRAJECTORY TRACKING OF AN AUTONOMOUS TWO-WHEELED MOBILE ROBOT

2005 ◽  
Vol 38 (1) ◽  
pp. 385-390 ◽  
Author(s):  
Martin Seyr ◽  
Stefan Jakubek ◽  
Gregor Novak
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Trajectory Tracking ◽  
Wheeled Mobile Robot

Feedforward and Feedback Kinematics Controller for Wheeled Mobile Robot Trajectory Tracking

2015 ◽  
Vol 3 (3) ◽  
pp. 178-182 ◽  
Author(s):  
Muhammad Asif ◽  
Muhammad Junaid Khan ◽  
Muhammad Safwan ◽  
Muhammad Rehan
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Wheeled Mobile Robot ◽  
Robot Trajectory

Motion modeling of a non-holonomic wheeled mobile robot based on trajectory tracking control

2020 ◽  
Vol 44 (2) ◽  
pp. 228-233
Author(s):  
Xuefeng Han ◽  
Mingda Ge ◽  
Jicheng Cui ◽  
Hao Wang ◽  
Wei Zhuang
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Kinematic Model ◽  
Wheeled Mobile Robot ◽  
Proportional Integral Derivative ◽  
Trajectory Tracking Control ◽  
Proportional Integral

Trajectory tracking is a problem of emphasis for the mobile robot. In this study, a coordinate transformation method was used to build a kinematic model of the wheeled mobile robot. A traditional proportional-integral-derivative control method was researched and improved by combining it with a neural network. A neural network proportional-integral-derivative trajectory tracking control method was thus designed, and a simulation experiment was performed using Simulink. The results show that in circular trajectory tracking control, the maximum errors of the X axis, Y axis, and θ were approximately 2.1 m, 2.3 m, and 0.4 rad, respectively, and that the system remained stable after running for 10 s. In straight-line trajectory tracking control, the maximum errors of the X axis, Y axis, and θ were approximately −0.8 m, 1.3 m, and 0.3 rad, respectively, and the system remained stable after running for 8 s. The error was relatively small, and the effect of trajectory tracking control was good. The studied method had good performance in terms of wheeled mobile robot trajectory tracking control and is worthy of further promotion and application.

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