• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.599-605
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• 2017

For an unmanned vehicle to be driven on the off-road terrain, it is necessary to consider the vehicle's stability. This paper suggests a path tracking controller for simulation of real-time vehicle stability analysis. The path tracking controller uses the preview distance to track the given trajectory. The disturbance moment is estimated using the yaw moment observer, and this information is used for compensation in the yaw moment control. On a curved path, the vehicle's desired velocity is determined from the curvature of the path. Because the vehicle is equipped with six independent motor driven wheels, the driving torques are distributed on all the wheels. The effectiveness of the path tracking controller is verified using ADAMS/MATLAB co-simulation.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2989-2991
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• 1999

We design the stable controller with variable gains and reference velocity in order to apply to this controller the proper gains and reference velocity generated with fuzzy logic in on-line. The proposed controller is applied to solve two problems including the reference velocity tracking problem and speedy tracking problem. The result of the simulation show a robust performance under the different conditions

• Journal of the Korean Society for Precision Engineering
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• v.19 no.8
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• pp.147-154
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• 2002

In this paper, a path navigation algorithm through use of a sensor platform is proposed. The sensor platform is composed of two electric motors which make panning and tilting motions. An algorithm for computing a real path and an obstacle length is developed by using a scanning method that controls rotation of the sensors on the platform. An Autonomous Robot Vehicle(ARV) can perceive the given path by adapting this algorithm. A sensor scanning method is applied to the sensor platform for using small numbers of sensor. The path navigation algorithm is composed of two parts. One is to perceive a path pattern, the other is used to avoid an obstacle. An optimal controller is designed for tracking the reference path which is generated by perceiving the path pattern. The ARV is operated using the optimal controller and the path navigation algorithm. Based on the results of actual experiments, this algorithm for an ARV proved sufficient for path navigation by small number of sensors and for a low cost controller by using the sensor platform with a scanning method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.640-645
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• 2004

This paper proposes a direct adaptive control method using self-recurrent wavelet neural network (SRWNN) for stable path tracking of mobile robots. The architecture of the SRWNN is a modified model of the wavelet neural network (WNN). Unlike the WNN, since a mother wavelet layer of the SRWNN is composed of self-feedback neurons, the SRWNN has the ability to store the past information of the wavelet. For this ability of the SRWNN, the SRWNN is used as a controller with simpler structure than the WNN in our on-line control process. The gradient-descent method with adaptive learning rates (ALR) is applied to train the parameters of the SRWNN. The ALR are derived from discrete Lyapunov stability theorem, which are used to guarantee the stable path tracking of mobile robots. Finally, through computer simulations, we demonstrate the effectiveness and stability of the proposed controller.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.786-791
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• 2003

This paper proposes an adaptive control algorithm for nonholonomic mobile robots with unknown parameters and the proposed control method is used in numerical simulations for applying to a practical twowheeled welding mobile robot(WMR). The proposed adaptive controller to track an arbitrary given welding path is designed by using back-stepping technique and is derived for a nonlinear model under the assumption such that the system parameters are partially known. Moreover, the proposed adaptive control system is stable in the sense of Lyapunov stability. Inertia moments of system are considered to be unknown parameters and their values can be estimated simply by using update laws proposed in an adaptive control scheme of this research. The simulation results are provided to show the effectiveness of the accurate tracking capability of the proposed controller for two-wheeled welding mobile robot with a smooth curved reference welding path.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.140-146
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• 2007

This paper demonstrates the development of a mobile robot for patrol. We fuse differential GPS, angle sensor and odometry data using the framework of extended Kalman filter to localize a mobile robot in outdoor environments. An important feature of road environment is the existence of curbs. So, we also propose an algorithm to find out the position of curbs from laser range finder data using Hough transform. The mobile robot builds the map of the curbs of roads and the map is used fur tracking and localization. The patrol robot system consists of a mobile robot and a control station. The mobile robot sends the image data from a camera to the control station. The remote control station receives and displays the image data. Also, the patrol robot system can be used in two modes, teleoperated or autonomous. In teleoperated mode, the teleoperator commands the mobile robot based on the image data. On the other hand, in autonomous mode, the mobile robot has to autonomously track the predefined waypoints. So, we have designed a path tracking controller to track the path. We have been able to confirm that the proposed algorithms show proper performances in outdoor environment through experiments in the road.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.12-18
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• 2010

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. Genetic algorithms are employed to optimize the fuzzy rules of FBFN. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.49-53
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• 2011

Path following of the mobile robot is one research hot for the mobile robot navigation. For the control system of the wheeled mobile robot(WMR) being in nonhonolomic system and the complex relations among the control parameters, it is difficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive following controller based on the PID for mobile robot path following. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity and orientation tracking control of the nonholonomic WMR. The simulation results of wheel type mobile robot platform are given to show the effectiveness of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1047-1051
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• 1993

A fuzzy controller of a manipulator with artificial rubber muscles is proposed. The fuzzy logic controller as a compensator is described to control the trajectory tracking of a -two link manipulator, where computed torque control method has already assumed to be applied. We shows that the fuzzy compensator with a simple adaptive scaling technique is effective for the robust control when there exist model uncertainties and/or untuned feedback gains. The effectiveness of the proposed control method is illustrated by some experimental results for a circular path tracking.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.307-310
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• 2001

Mobile AGV is one of the nonholon-omic systems. The integration of the kinematic adaptive controller for the dynamic in this pa-per introduction a motion control problem's dynamic state feedback as well as output feedback tracking laws will be constructed with the adaptive extension of the controller is proposed. Feedback control strategies for mobile AGV are important to compensate for disturabances and errors in the initial condition. The problems of path following or tracking and of stabilization about a constant configuration have been treated as separate problems for nonholonomic mobile AGV.