Research On Trajectory Tracking Control Methods Of Car-like Mobile Robot

With the development of robot technology, the trajectory-tracking problem of mobile robot is paid more and more attention. A wheeled car-like mobile robot, which is steered by two front wheels and driven by two rear wheels, has similar kinematic model to that of a four-wheel car. So the study on the trajectory-tracking problem of the wheeled car-like mobile robot is significant for automatic drive of car as well as intelligent transportation. Due to the intrinsic non-holonomic kinematical constraints of car-like robot, it is challenging to control the robot track the given trajectory.Firstly, the lateral trajectory-tracking problem is studied when the robot moves in low speed or parameters change little. Three methods, which include the classic PID, radial basis function (RBF) neural network based adaptive PID and fuzzy self-tuning PID, are adopted for the mobile robot to realize lateral control of trajectory tracking. To control the longitudinal speed of the robot, a fuzzy speed controller is designed based on the preview control theory. Secondly, a global asymptotically stable tracking controller is designed using the backstepping method on the basis of the kinematic model of the car-like robot. Meanwhile, the Lyapunov theory is used to verify the stability of the controller.Considering the kinematic constraints, the speed limited strategy is introduced to ensure the smooth motion of the robot.The validity of three lateral control methods as well as the backstepping method is simulated with MATLAB. The merit and applicability of each method are analyzed and compared. Finally, initial trajectory-tracking experiments are implemented, in which a CMOS camera is used to acquire trajectory information. Experimental results show that, with the methods presented in this paper, the robot can track the paved trajectory well.