• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.853-858
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• 2016

Cooperation and collaboration with robots are key functions of robotic utility that are currently developing. Thus, robots should be safe and resemble human beings to cope with these needs. In particular, dual-arm robots that mimic human kinetics are becoming the focus of recent industrial robotics research. Their size is similar to the size of a human adult; however, they lack natural, human-like motion. One of the critical reasons for this is the shoulder complex. Most recent dual-arm robots have only 2 degrees of freedoms (DOFs), which significantly limits the workspace and mobility of the shoulders and arms. Therefore, a redundant shoulder complex could be very important in new developments that enable new capabilities. However, constructing a kinematically redundant shoulder complex is difficult because of spatial constraints. Therefore, we propose a novel, redundant shoulder complex for a human-like robot that is driven by flexible wire tendons. This kinematically redundant shoulder complex allows human-like robots to move more naturally because of redundant DOFs. To control the proposed shoulder complex, a hybrid control scheme is used. The positioning precision has also been considered, and the ability of the shoulder complex to perform several human-like motions has been verified.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.260-263
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• 2003

This paper has developed the computer integration manufacturing system and Internet based tele-operations. The functions of CIMS include production planing, material requirement planning, work order generation, process control, quality control, shipping planning, warehouse and inventory management and material cost accounting.[1] In this paper focuses on the automatic warehouse control and inventory management by developing the information system as well as the Internet-based integration. The system overview is divided into three parts, the mechanical system, the computer and developed software to control and manage the information and the communication system. The mechanical system consists of the warehouse machine and forklift mobile robot controlled by programmable logic controller (PLC). The computer works on many functions such as control station interfaces with PLC, managing database and inventory, and Internet server to broadcast the inventory database to users via World Wide Web and monitoring the operation on web camera. Our scheme the inventory database can be checked easily anywhere and anytime when the users connect to the Internet. In this article, the lead-time and inventory level can be reduced therefore the holding cost and operating time is also decreased.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.447-457
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• 2019

The intelligent sensory system is required to ensure the accurate welding performance. This paper describes the development of an intelligent vision sensor for the robotic laser welding. The sensor system includes a PC based vision camera and a stripe-type laser diode. A set of robust image processing algorithms are implemented. The laser-stripe sensor can measure the profile of the welding object and obtain the seam line. Moreover, the working distance of the sensor can be changed and other configuration is adjusted accordingly. The robot, the seam tracking system, and CW Nd:YAG laser are used for the laser welding robot system. The simple and efficient control scheme of the whole system is also presented. The profile measurement and the seam tracking experiments were carried out to validate the operation of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.123-126
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• 1998

The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the Meaning of these foundational concepts, simple genetic algorithm(SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithms. In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. So we propose a co-evolutionary method finding optimal fuzzy rules. Our algorithm is that after constructing two population groups m de up of rule vase and its schema, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the proposed method to a path planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.120-129
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• 1992

In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.158-163
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• 1998

This paper is our first attempt to construct a information processing system such as the living creatures' brain based on artificial life technique. In this paper, we propose a method of constructing neural networks using bio-inspired emergent and evolutionary concept, Ontogeny of living things is realized by cellular automata model and Phylogeny that is living things adaptation ability themselves to given environment, are realized by evolutionary algorithms. Proposing evolving cellular automata neural systems are calledin a word ECANS. A basic component of ECANS is 'cell' which is modeled on chaotic neuron with complex characteristics, In our system, the states of cell are classified into eight by method of connection neighborhood cells. When a problem is given, ECANS adapt itself to the problem by evolutionary method. For fixed cells transition rule, the structure of neural network is adapted by change of initial cell' arrangement. This initial cell is to become a network b developmental process. The effectiveness and the capability of proposed scheme are verified by applying it to pattern classification and robot control problem.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2365-2377
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• 2017

This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from "explosion of complexity", a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of "explosion of complexity", and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.890-893
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• 1999

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are demonstrate the effectiveness of the Proposed learning using the DNP.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.712-715
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• 1999

The goal of this paper is to provide a Graphic man-machine interface that can be used to control multiple robots simultaneously. The proposed GUI scheme gave emphasis on making multiple robots Perform the cooperative works, maintaining a given formation. It controls multiple robots in two different modes. : a group mode and a individual mode. In the group mode, a common goal position and formation are delivered to individual robots at the same time, and in the individual mode one robot is selected. o increase the efficiency of the interface, a time scheduler is provided. The experimental results are included.

• Journal of Mechanical Science and Technology
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• v.18 no.10
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• pp.1691-1699
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• 2004

The objective of this study is to present an accurate and simple method to describe the motion of constrained mechanical or structural systems. The proposed method is an elimination method to require less effort in computing Moore-Penrose inverse matrix than the generalized inverse method provided by Udwadia and Kalaba. Considering that the results by numerical integration of the derived second-order differential equation to describe constrained motion veer away the constrained trajectories, this study presents a numerical integration scheme to obtain more accurate results. Applications of holonomically or nonholonomically constrained systems illustrate the validity and effectiveness of the proposed method.