• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1238-1245
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• 2014

This paper proposes an RBFN-based adaptive tracking controller for an electrically driven mobile robot with parametric uncertainties and external disturbances. A mobile robot model considered in this paper includes all models of the robot body and actuators with uncertain kinematic and dynamic parameters, and uncertain frictions and external disturbances. The proposed controller consists of an RBFN(Radial Basis Function Network) and a robust adaptive controller. The presented RBFN is used to approximate unknown nonlinear robot dynamic functions. The proposed controller is adjusted by the adaptation laws obtained through the Lyapunov stability analysis. The proposed control scheme does not a priori need the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. Also, nominal parameter values are not required in the controller. The global stability of the closed-loop robot control system is guaranteed using the Lyapunov stability theory. Simulation results show the validity and robustness of the proposed control scheme.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.370-377
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• 2010

An Intelligent service robot performs various complex tasks in dynamic environment, providing useful intelligent services for human users. The robot needs to continuously monitor dynamically changing environment and reactively choose the best behavior for the changing context. The selected behaviors may include nondeterministic or parallel actions. In this paper, we present a structured reactive robot programming language, SPRIT that is based on Structured Circuit Semantics (SCS). SPRIT is fully implemented as a task executor and tested for reactive robot tasks in dynamic environment to show that it can be used to explicitly represent and effectively implement the complex reactive behaviors of intelligent robot systems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.411-416
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• 2000

Cutting process has been automated by progress of CNC and CAD/CAM, but polishing process has been depended on only experiential knowledge of expert. To automate the polishing process, a polishing robot with w degrees of freedom which is attached to a machining center with 3 degrees of freedom has been developed. This automatic polishing robot is able to keep the polishing tool normal on the curved surface of die to improve a performance of polishing. Polishing task for a curved surface die demands repetitive operation and high precision, but conventional control algorithm can not cope with the problem of disturbance such as a change of load. In this research, a new sliding mode control algorithm is applied to the robot. The signal compression method is used to identify polishing robot system. to obtain an effect of 5 degrees of freedom motion, a synchronization between the machining center and polishing robot is accomplished by using M code of machining center. And also a trajectory for polishing the curved surface die by 5 degrees of freedom motion, a synchronization between the machining center and polishing robot is accomplished by using M code of machining center. And also a trajectory for polishing the curved surface die by 5 axes machining center is divided into data of two types for 3 axes machining center and 2 axes polishing robot. To evaluate polishing performance of the robot. various experiments are carried out.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.538-542
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• 2009

Industrial manipulators have been mostly used in large companies such as automakers and electronics companies. In recent years, however, demands for industrial manipulators from small and medium-sized enterprises are on the increase because of shortage of manpower and high wages. Since these companies cannot hire robot engineers for operation and programming of a robot, intuitive teaching and playback techniques of a robot manipulator should replace the robot programming which requires substantial knowledge of a robot. This paper proposes an intuitive teaching and playback algorithm used in assembly tasks. An operator can directly teach the robot by grasping the end-effector and moving it to the desired point in the teaching phase. The 6 axis force/torque sensor attached to the manipulator end-effector is used to sense the human intention in teaching the robot. After this teaching phase, a robot can track the target position or trajectory accurately in the playback phase. When the robot contacts the environment during the teaching and playback phases, impedance control is conducted to make the contact task stable. Peg-in-hole experiments are selected to validate the proposed algorithm since this task can describe the important features of various assembly tasks which require both accurate position and force control. It is shown that the proposed teaching and playback algorithm provides high positioning accuracy and stable contact tasks.

• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.11-22
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• 2011

The purpose of the research is examine the effect of STEM integration education using educatinal robot on academic achievement and subject Attitude of mathematics and science. The participants were 73 students of two classes, sampled from 6th graders of an elementary school. They were divided into a control group who learned a traditional mathematics and sciences education based textbooks and an experimental group who learned STEM integration education using educational robot during 12 sessions. The results are summarized as follows : First, there is a significant difference in academic achievement between two groups. STEM integration education using educational robot based group accomplished higher achievement than textbook based instruction group. Especially, post test analyzes results on the three factors of academic achievement, knowledge, understanding and adaptation, indicate statistically meaningful difference between two groups in understanding and adaptation area except knowledge area. Second, it shows that it greatly affected a positive influence on experimental group's attitude toward subjects in affective area. So we can expect STEM integration education using educational robot to be an alternative for stimulating children's higher learning interest on mathematics and science subject.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.280-285
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• 1991

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, a learning control architecture for the dynamic control of a robot manipulator is developed using inverse dynamic neurocontroller and linear neurocontroher. The inverse dynamic neurocontrouer consists of a MLP (multi-layer perceptron) and the linear neurocontroller consists of SLPs (single layer perceptron). Compared with the previous type of neurocontroller which is using an inverse dynamic neurocontroller and a fixed PD gain controller, proposed architecture shows the superior performance over the previous type of neurocontroller because linear neurocontroller can adapt its gain according to the applied task. This superior performance is tested and verified through the control of PUMA 560. Without any knowledge on the dynamic model, its parameters of a robot , (The robot is treated as a complete black box), the neurocontroller, through practice, gradually and implicitly learns the robot's dynamic properties which is essential for fast and accurate control.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.607-612
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• 2008

This paper proposes a robot visual servo approach based on image appearance and a wavelet function neural network. The inputs of the wavelet neural network are changes of image features or the elements of image appearance vector, and the outputs are changes of robot joint angles. Image appearance vector is calculated by using eigen subspace transform algorithm. The proposed approach does not need a priori knowledge of the robot kinematics, hand-eye geometry and camera models. The experiment results on a real robot system show that the proposed method is practical and simple.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.305-307
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• 1994

In this paper, the desist and the implementation of a robust adaptive controller for trajectory tracking control of the robot manipulator is presented. The proposed control scheme ensures that without any prior knowledge of the robot manipulator parameters, tracking errors are converged to some boundary in the presence of a state-dependent input disturbances as well as the ideal case. The 3 DOF robot manipulator including actuator dynamics is used for the implementation of the proposed control scheme. The experimental results show that the proposed control scheme is valid for trajectory tracking control of the robot manipulator.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.49-60
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• 1999

This paper addresses a welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in the welding process planning, it has not been considered through a systematic approach, but it depends rather on empirical knowledge. Thus, an effective task sequencing for robot arc welding is required. Welding perations can be classified by the number of welding robots. Genetic algorithms are applied to tackle those welding task sequencing problems. A genetic algorithm for traveling salesman problem (TSP) is utilized to determine welding task sequencing for a MultiWeldline-SingleLayer problem. Further, welding task sequencing for multiWeldline-MultiLayer welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is also proposed to solve multi-robot welding sequencing : MultiWeldline with multi robots. Finally, the genetic algorithm are implemented for the welding task sequencing of three dimensional weld plate assemblies. Robot welding operations conforming to the algorithms are simulated in graphic detail using a robot simulation software IGRIP.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.48-54
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• 2007

A network-based robot [1] is a robot that explores service servers in the network environment for analyzing sensor data and making decision. Since network-based robot architecture was proposed, it's possible to reduce costs of robots. We hope robots would be all around at home environment. Therefore, normal users who are not experts need to be able to control those robots by using easy commands. We developed a scripting language, named CCSLR, to help users and developers who control various robots in ubiquitous environment. We focused on how to design the common language for various robots and how to translate a CCSLR script into a sequence of low-level commands of the target robot. In this paper, we propose scripting methods, with three layers. The CCSLR system reads the profile information from the knowledge representation database. Users don't have to know all about kinematical and mechanical details of a robot. Then again, the CCSLR system will use the profile information to translate the script into separated executable library commands. The CCSLR system manages robot's changing state every time a robot executes a command.