• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.6
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• pp.731-737
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• 1999

This paper describes the path tracking control for a mobile robot which has two casters at the front and rear to keep balance and two driving wheels on the left and right sides of its body. Power wheeled steering method is adapted to control heading of the robot. It is very difficult to find appropriate feedback gains when linear regulator control scheme is adapted to path tracking con-trol of this type of robot. Therefore in this paper we propose the path tracking control algorithm using the fuzzy logic control scheme for this type of root. Simulation to prove the validity of the proposed two algorithms is performed. The results are reported as last part in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.142-147
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• 1988

Free-path-type guidance system does not need a hardwired path in the environment so that it gives a mobile robot a flexible path. ln this study to achieve the free-path-type guidance system for a mobile robot which is steered by the differential steering of both drive forewheels, position recognition systems are constructed using odometer system as an internal position sensor. Two odometer systems, a auxiliary wheel odometer and a 2-encoder odometer system are constructed and path following algorithms using these odometer systems are designed and experimented. PID control type is adopted in the path following algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.710-715
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• 1990

This paper presents a path control method for mobile robot using neural network and a systematic method for the kinematic and dynamic modelling of a mobile robot. The robot finds its path deviation by taking the signals of an optical array sensor and determined its moving behaviors using neural net control method. A robot can be taught behaviors by changing the given patterns, in this work, Back Propagation rule is used as a learning method.

• 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.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.259-268
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• 2011

A robot education system by emulation based on Web can be efficiently used for understanding concept of robot assembly practice and control mechanism of robot by control programming. It is important to predict the path of the line tracer robot which has to be decided by the robot. Shortest Path Algorithm is a well known algorithm which searches the most efficient path between the start node and the end node. There are two related typical algorithms. Dijkstra Algorithm searches the shortest path tree from a node to the rest of the other nodes. $A^*$ Algorithm searches the shortest paths among all nodes. The delay time caused by turning the direction of navigation for the line tracer robot at the crossroads can give big differences to the travel time of the robot. So we need an efficient path determine algorithm which can solve this problem. Thus, It is necessary to analyze the overhead of changing direction of robot at multi-linked node to determine the next direction for efficient routings. In this paper, we reflect the real delay time of directional changing from the real robot. A speed based Dijkstra algorithm is proposed and compared with the previous ones to analyze the performance.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.917-928
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• 2006

In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines, including robot control, where they can be used to solve nonlinear control problems. One of these ANNs applications is that of the inverse kinematic problem, which is important in robot path planning. In this paper, a neural network is employed to analyse of inverse kinematics of PUMA 560 type robot. The neural network is designed to find exact kinematics of the robot. The neural network is a feedforward neural network (FNN). The FNN is trained with different types of learning algorithm for designing exact inverse model of the robot. The Unimation PUMA 560 is a robot with six degrees of freedom and rotational joints. Inverse neural network model of the robot is trained with different learning algorithms for finding exact model of the robot. From the simulation results, the proposed neural network has superior performance for modelling complex robot's kinematics.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.253-253
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• 2000

Each robot plays a role of its own behavior in dynamic robot-soccer environment. One of the most necessary conditions to win a game is control of robot movement. In this paper we suggest a win strategy using Cellular Neural Network to set optimal path and cooperative behavior, which divides a soccer ground into grid-cell based ground and has robots move a next grid-cell along the optimal path to approach the moving target.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.77-86
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• 2006

A new method in robot path generation is presented using an analysis of the characteristics of multi-robot collision avoidance. The research is based on the concept of the collision map, where the collision between two robots is presented by a collision region and a crossing curve TLVSTC (traveled length versus servo time curve). Analytic collision avoidance is considered by translating the collision region in the collision map. The 4 different translations of collision regions correspond to the 4 parallel movements of the actual original robot path in the real world. This analysis is applied to path modifications where the analysis of collision characteristics is crucial and the resultant path for collision avoidance is generated. Also, the correlations between the translations of the collision region and robot paths are clarified by analyzing the collision/non-collision areas. The influence of the changes of robot velocity is investigated analytically in view of collision avoidance as an example.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.231-236
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• 1997

We propose the hybrid control for the path control of wheeled mobile robot system. To develop the hybrid control of mobile robot, the continuous dynamics of mobile robot are modeled by the switched systems. The abstract model and digital automata for the path control are developed. This hybrid control system has the 3-layered hierachical structure : digital automata as the higher process, mobile robot system as the lower process, and the interface as the interaction process between the continuous dynamics and the discrete dynamics. The control of following the desired-paths with edges are investigated as the applications by the computer simulation.