• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.999-1010
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• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. This maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulators because hydraulic manipulators have the advantage of electric insulation and power/mass density. Meanwhile an electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of an electrically driven manipulator. So it is relatively difficult to realize not only stable contact work but also accurate force control for the autonomous assembly tasks using hydraulic manipulators. In this paper, the robust force control of a 6-link electro-hydraulic manipulator system used in the real maintenance task of active electric lines is examined in detail. A nominal model for the system is obtained from experimental frequency responses of the system, and the deviation of the manipulator system from the nominal model is derived by a multiplicative uncertainty. Robust disturbance observers for force control are designed using this information in an H$\_$$\infty$/ framework, and implemented on the two different setups. Experimental results show that highly robust force tracking by a 6-link electro-hydraulic manipulator could be achieved even if the stiffness of environment and the shape of wall change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.859-869
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• 2008

These days, almost every industry's production line has become automatic and this phenomenon brought a lot of benefits such as increase in productivity and economical effect, assurance in industrial safety, better quality and compatibility. However, unlike industrial production line, in construction industry, automation has number of barriers like uncertainty incidents and intellectual judgment to make ability to make solution out of it. Therefore construction industry is still demanding use of construction machine through labor. Due to this matter operational labor in construction industry is aging and fading. To solve these problem, in developed nations like Europe, US or Japan are keep researching for the automation in construction and road pavement, strengthening and some other simple operations have been worked through automation but in civil engineering site, automation research is still low despite of its importance in constructional site. For automating civil engineering operation, effective operational plan have to be set by analyzing ground information acquainted. If skillful worker apply heuristics, trial & error can be reduced with increased safety and the effective work plan can be established. Hence, this research will introduce Intellectual Task Planning System for Intelligent Excavating System's effective work plan and heuristics applied in each steps.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.212-218
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• 2008

Collision avoidance is a fundamental and important task of an autonomous mobile robot for safe navigation in real environments with high uncertainty. Obstacles are classified into static and dynamic obstacles. It is difficult to avoid dynamic obstacles because the positions of dynamic obstacles are likely to change at any time. This paper proposes a scheme for vision-based avoidance of dynamic obstacles. This approach extracts object candidates that can be considered moving objects based on the labeling algorithm using depth information. Then it detects moving objects among object candidates using motion vectors. In case the motion vectors are not extracted, it can still detect the moving objects stably through their color information. A robot avoids the dynamic obstacle using the dynamic window approach (DWA) with the object path estimated from the information of the detected obstacles. The DWA is a well known technique for reactive collision avoidance. This paper also proposes an algorithm which autonomously registers the obstacle color. Therefore, a robot can navigate more safely and efficiently with the proposed scheme.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.119-122
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• 2002

The research Interest of this paper is focused on the efficient clustering task for an arbitrary color data. In order to tackle this problem, we have tiled to model the inherent uncertainty and vagueness of color data using fuzzy color model. By laking a fuzzy approach to color modeling, we could make a soft decision for the vague regions between neighboring colors. The proposed fuzzy color model defined a three dimensional fuzzy color ball and color membership computation method with the two inter-color distance measures. With the fuzzy color model, we developed a new fuzzy clustering algorithm for an efficient partition of color data. Each fuzzy cluster set has a cluster prototype which is represented by fuzzy color centroid.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.11
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• pp.1272-1278
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• 2011

Mechanisms of the robot system should be developed according to the task. In this study, we propose improving adaptability of the robot mechanism with the modularized joint mechanism. Adaptability is the measure of the system ability to cope with change or uncertainty. Modular type joint has been widely used in development of various robots including reconfigurable robots. To build robotic systems more flexibly and quickly with low costs of manufacturing and maintenance, we have designed a modular type joint with one degree of freedom for general purpose. This module is designed to be compact, light-weight and self-controlled. In this design, we consider the kinematics and dynamics properties of the modular type joint.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.91-99
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• 2020

Fruit and vegetable harvesting robots have been widely studied and developed in recent years to reduce the cost of harvesting tasks such as labor and time. However, harvesting robots have many challenges due to the difficulty and uncertainty of task. In this paper, we characterize the crop environment related to the harvesting robot and analyzes state-of-the-art of the harvesting robot especially, in the viewpoint of robotic end-effector. The end-effector, an one of most important element of the harvesting robot, was classified into gripper and harvesting module, which were reviewed in more detail. Performance measures for the evaluation of harvesting robot such as test, detachment success, harvest success, and cycle time were also introduced. Furthermore, we discuss the current limitations of the harvesting robot and challenges and directions for future research.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.266-278
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• 1987

This paper addresses the issues in setting performance criteria for safety regulation of nuclear power plants. Since setting criteria at the low level is a much more difficult task than it is at the top level, the low-level performance criteria should be derived consistently from the more easily determinable top-level performance criteria. The paper also proposes several approaches to characterizing uncertainties in performance criteria, by extending the reliability allocation methodology that is based on the mean-to-mean mapping to a stochastic multi-objective optimization problem where the state variables are uncertain.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.5-129
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• 2001

When a robot manipulator performs some task like grinding or assembling, not only the position control but also the force control of the tools connected to the robot must be controlled. But at this time We were received the uncertainty problems of system information for the force control, for example disturbance, senor resolution and measurement noise. Therefore we proposed fuzzy logic control method instead of existing control theory for the robot manipulator control, for example PID control method. In this paper, We proposed hybrid position/force control of robot manipulator using fuzzy logic control method. To show the validity of the proposed fuzzy controller, We compared fuzzy controller with conventional PID controller.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.363-378
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• 2015

Estimation of geotechnical properties is an essential but challenging task since they are major components governing the safety and reliability of the entire structural system. However, due to time and budget constraints, reliable geotechnical properties estimation using traditional site characterization approach is difficult. In view of this, an alternative efficient and cost effective approach to address the overall uncertainty is necessary to facilitate an economical, safe and reliable geotechnical design. In this paper a probabilistic approach is proposed for real-time updating by incorporating new geotechnical information from the underlying project site. The updated model obtained from the proposed method is advantageous because it incorporates information from both existing database and the site of concern. An application using real data from a site in Hong Kong will be presented to demonstrate the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1072-1077
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• 1992

In ths paper a new active assembly algorithm for chamferless precision parts mating, is considered. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly mehtod alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as imperfect knowledge of the parts being assembled as well as the limitation of the devices performing the assebled as well as the limitation of the devices performing the assembly. To cope with these problems, a self-learning rule-based assembly algorithm is proposed by intergaring fuzzy set theory and neural network. In this algortihm, fuzzy set theory copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly schemen so as to learn fuzzy rules form experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly algorithm is evaluated through a series of experiments. The results show that the self-learning fuzzy assembly scheme can be effecitively applied to chamferless precision parts mating.