• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.852-862
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• 2013

This paper proposes a target tracking control method for wheeled mobile robots with nonholonomic constraints by using a backstepping-like feedback linearization. For the target tracking, we apply a vision system to mobile robots to obtain the relative posture information between the mobile robot and the target. The robots do not use the sensors to obtain the velocity information in this paper and therefore assumed the unknown velocities of both mobile robot and target. Instead, the proposed method uses only the maximum velocity information of the mobile robot and target. First, the pseudo command for the forward linear velocity and the heading direction angle are designed based on the kinematics by using the obtained image information. Then, the actual control inputs are designed to make the actual forward linear velocity and the heading direction angle follow the pseudo commands. Through simulations and experiments for the mobile robot we have confirmed that the proposed control method is able to track target even when the velocity sensors are not used at all.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.195-200
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• 2000

This paper describes the path planning method in an unknown environment for an autonomous mobile robot equipped with CCD(Charge-Coupled Device) camera. The mobile robot moves along the guideline. The CCD camera is used for the detection of the existence of a guideline. The wavelet transform is used to find the edge of guideline. It is possible for us to do image processing more easily and rapidly by using wavelet transform. We make a fuzzy control rule using image data as an input then determined the position and the navigation of the mobile robot. The center value of guideline is the input of fuzzy logic controller and the steering angle of the mobile robot is the fuzzy controller output. Some actual experiments show that the mobile robot effectively moves to target position by means of the applied fuzzy control.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.5 s.170
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• pp.95-102
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• 2005

The coordination of locomotion and manipulation has been the typical and main issue for a mobile manipulator. This is particularly because the solution for the control parameters is redundant and the accuracies of controlling the each joints are different. This paper presents a motion planning method for which the mobile base locomotion is less precise than the manipulator control. In such a case, it is appropriate to move the mobile base to discrete poses and then to move the manipulator to track a prescribed path of the end effector, while the base is stationary. It uses a variant of the conventional manipulability measure that is developed for the trajectory control of the end effector of the mobile manipulator along an arbitrary path in the three dimensional space. The proposed method was implemented on the simulation and the experiments of a mobile manipulator and showed its effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.556-559
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• 1997

In this paper, we propose a cooperative multi-robot control algorithm. Specifically, the cooperative task is that two mobile robots should transfer a long rigid object along a predefined path. To resolve the problem, we introduce the master-slave concept for two mobile robots, which have the same structure. According to the velocity of the master robot and the positions of two robots on the path, the velocity of the slave robot is determined. In case that the robots can't move further, the role of the robot is interchanged. The effectiveness of this decentralized algorithm is proved by computer simulations.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.942-946
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• 2005

In this paper, we propose that the mutual cooperative control in the chaotic mobile robot. In order to achieve mutual cooperative control in the mobile robot, we apply coupled synchronization technique and driven synchronization technique in the mobile robot with obstacle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.355-359
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• 2005

In this paper, we propose that the synchronization method for mutual cooperative control in the mobile robot. In order to achieve the synchronization for mutual cooperative control in the mobile robot, we apply coupled synchronization technique and driven synchronization technique in the mobile robot with obstacle.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.197-203
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• 2006

This paper addresses dynamic modeling and task-space trajectory following issues for nonholonomic mobile manipulators moving on a slope. An integrated dynamic modeling method is proposed considering nonholonomic constraints and interactive motions. An adaptive neural-fuzzy controller is presented for end-effector trajectory following, which does not rely on precise apriori knowledge of dynamic parameters and can suppress bounded external disturbances. Effectiveness of the proposed algorithm is verified through simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2498-2501
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• 2003

In this paper, we present a wavelet neural network (WNN) approach to the solution of the path tracking problem for mobile robots that possess complexity, nonlinearity and noise. First, we discuss a WNN based control system where the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot. This compact network structure is helpful to determine the number of hidden nodes and the initial value of weights. Then, the data with various noises provided by odometric and external sensors are here fused together by means of an Extended Kalman Filter (EKF) approach for the pose estimation problem of mobile robots. This control process is a dynamic on-line process that uses the wavelet neural network trained via the gradient-descent method with estimates from EKF. Finally, we verify the effectiveness and feasibility of the proposed control system through simulations.