• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.94-101
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• 2006

A global path planning method using self-organizing feature map which is a method among a number of neural network is presented. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are moved toward the input vector On the other hand, the modified method in this research uses a predetermined initial weight vectors of 1-dimensional string and 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are moved toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.133.6-133
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• 2001

Reactor vessel is one of the most important equipment of Nuclear Power Plant (NPP) with regard to the nuclear safety. Thus reactor vessel must be examined periodically by certified experts. Currently, ultra-sonic(UT) non-destructive inspection is executed on reactor vessel. Two different techniques are used in this inspection. One is using the movable manipulator fixed with the support-guide placed on the vessel, and the other is using mobile robot moving in the vessel. Movable manipulator machine is very heavy, hard to handle, and very expensive. Mobile robot equipment is small and convenient but has a weak point on positional precision. To solve these problems we developed a reactor inspection system based on laser-driven mobile robot. This paper describes the main concept and structure of integrated inspection units and the feature of implemented units.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.4
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• pp.69-76
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• 2008

The self-organizing feature map(SOFM) among a number of neural network uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are moved toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors of the 1-dimensional string, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the opposite direction of input vector. According to simulation results one can conclude that the method using string and the modified neural network is useful tool to mobile robot for the global path planning.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.473-479
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• 2006

A global path planning algorithm using modified self-organizing feature map(SOFM) which is a method among a number of neural network is presented. The SOFM uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors of the 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the opposite direction of input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.2
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• pp.53-63
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• 2018

A novel real-time path planning algorithm suitable for implementation on a small mobile robot is introduced. The algorithm can be used as the basis for mapping unknown or partially known environments and is tested in a specially developed simulation environment in Matlab(R). Simulations results are presented demonstrating that the algorithm can readily be implemented to allow a small robot to navigate in various unknown and partially known environments. The main characteristics of the algorithm include simplicity, ease of implementation, speed, and efficiency, thereby being especially suitable for small robots. Furthermore, for partially known environments, another algorithm is proposed to predefine an optimal path taking into account information provided regarding the environment.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.520-522
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• 2004

In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers. It has an advantage of fast planning and simple operation. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in any direction. When a robot meets moving obstacles, it avoids obstacles in a random direction. Sonar ranger is useful to get obstacle information and RAS may be a good solution for path planning.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.2
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• pp.112-117
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• 2016

In the construction industry, concrete polishing is used to grind and rub the surface of concrete grounds with polishing machines to increase the strength of the concrete after deposition. Polishing is performed manually in spite of the generation of dust and the requirement of frequent replacements of the polishing pad. The concrete polishing robot developed in this research is a novel polishing automation system for preventing the workers from being exposed to poor working environments. This robot is able to change multiple polishing tools automatically; however, the workers can conveniently replace the worn-out polishing pads with new ones. The mobile platform of the polishing robot employs omnidirectional wheels to enable a flexible motion even in small and complicated workspaces. To evaluate the performance of the developed concrete polishing robot, extensive experiments including square trajectory tracking, automatic tool changing, actual polishing, and path generation simulation were performed.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.35-41
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• 2018

Smart device has become an affordable main computing resource for robotic ap-plications in accordance with a fast growth of mobile internet environment. Since the computing power of smart device has been increased, smart device based ro-bot system attempts to replace traditional robot applications with laptop-based system. Methodologies for acquisition of remote sensory information and control of various types of robots using smart device have been proposed recently. In this paper, we propose a robot control system using a monitoring program and a communication protocol. The proposed system is a combination of an educa-tional programming oriented robot named EPOR-S. as small service robot plat-form and a smart device. Through a simulation study using image processing, the feasibility of combination of the proposed robot monitoring program and control system was verified.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.319-326
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• 2014

Accurate estimation of the robot's position has an important role in autonomous navigation. Odometry is one of the most widely used techniques for mobile robot positioning. However, odometry has a well-known drawback that the position errors are accumulated when the travel distance increases. The UMBmark method is the conventional odometry calibration scheme for two wheel differential mobile robots. In the UMBmark method, the approximations for small angles are used in order to simplify the calculations. In this paper, we propose the new calibration scheme by using experimental orientation errors. Kinematic parameters can be calculated accurately without approximations by using experimental orientation errors. The numerical simulation and experimental results show that the odometry accuracy can be improved by the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.164-169
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• 1998

Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement", of multiple autonomous mobile robots are represented by a small number of fuzzy rules. Fuzzy rules in Sugeno type and their related paramenters are automatically generated from clustering input-output data obtained from the algorithms the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.