• Journal of the Korean Society for Precision Engineering
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• v.25 no.8
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• pp.37-44
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• 2008

Nowadays, the increasing global competition forces manufacturer to reduce the cost and time for implementation of manufacturing system. The AR(augmented reality) technology as a new human-machine interface introduces a noteworthy perspective for a new manufacturing system design. Using AR technology, a physically existing production environment can be superimposed with virtual planning objects. Therefore, the planning tasks can be validated without modeling the surrounding environment of the production domain during short process planning time. In this paper, we introduce the construction of AR browser and determine the optimal environment parameters for field application of AR system through lots of tests. And, many methods such as multi-marker coordinate system, division of virtual objects and so on, are proposed in order to solve the problems suggested from initial field test. Based on these tests and results, the test-bed of C/Pad assembly system is configured and robot program for C/Pad assembly is generated based on AR system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.211-217
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• 2014

This paper addresses an algorithm of path planning for autonomous driving of a ground vehicle in waypoint navigation. The proposed algorithm is flexible in utilization under a large GPS positioning error and generates collision-free multiple paths while pursuing minimum traveling time. An optimal path reduces inefficient steering by minimizing lateral changes in generated waypoints along a path. Simulation results compare the proposed algorithm with the A* algorithm by manipulation of the steering wheel and traveling time, and show that the proposed algorithm realizes real-time obstacle avoidance by quick processing of path generation, and minimum time traveling by producing paths with small lateral changes while overcoming the very irregular positioning error from the GPS.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1110-1119
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• 2003

This paper deals with the synthesis of the 3-dimensional grasp planning for unknown objects. Previous studies have many problems, which the estimation time for finding the grasping points is much long and the analysis used the not-perfect 3-dimensional modeling. To overcome these limitations in this paper new algorithm is proposed, which algorithm is achieved by two steps. First step is to find the whole 3-dimensional geometrical modeling for unknown objects by using stereo matching. Second step is to find the optimal grasping points for unknown objects by using the neural network trained by the result of optimization using genetic algorithm. The algorithm is verified by computer simulation, comparing the result between neural network and optimization.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.133-136
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• 1996

The nozzle dam task is essentially needed to maintain and repair nuclear power plants. For this task, an 8-dof redundant robot is studied with a local path-planning method[l] which is effective to find the optimal joint path in the constrained environment. In this paper, the method[l] is improved practically with the weight matrix and efficient algorithm to find working set. The effectiveness of the proposed method is demonstrated by simulation and animation.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.510-517
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• 2019

Efficient path planning is essential for unmanned surface vehicle (USV) navigation. The A^* algorithm is an effective algorithm for identifying a safe path with optimal distance cost. In this study, a modified version of the A^* algorithm is applied for planning the path of a USV in a static and dynamic obstacle environment. The current study adopts the A^* approach while maintaining a safe distance between the USV and obstacles. Two important parameters-path length and computational time-are considered at various start times. The results demonstrate that the modified approach is effective for obstacle avoidance by a USV that is compliant with the International Regulations for Preventing Collision at Sea (COLREGs).

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.68-77
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• 2006

Nowadays, the increasing global competition forces automobile manufacturer to increase quality and to reduce the cost and time for manufacturing planning. To solve these problems, automobile manufacturers try to apply digital manufacturing technologies. In this paper, a concept of method for planning the digital assembly system is proposed. Based on the requirements of assembly tasks obtained through product analysis, the function and sequence modeling for assembly process is executed using the IDEF0 and UML model. For implementation of digital assembly system, the selected components are modeled by using 3D CAD tools. According to the system configuration strategy, lots of the alternative solutions for the assembly system are generated. Finally, the optimal assembly system is chosen by the evaluation of the alternative solutions with TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) method. According to proposed procedure, digital laser welding system is implemented in DELMIA.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.170-174
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• 2003

In this research, we consider an integrated manufacturing/distribution planning problem in supply chain (SC) which has non-integer time lags. We focus on a capacitated manufacturing planning and capacity allocation problem for the system. We develop a mixed binary integer linear programming (MBLP) model and propose an efficient heuristic procedure using an adaptive genetic algorithm, which is composed of a regeneration procedure for evaluating infeasible chromosomes and the reduced costs from the LP-relaxation of the original model. The proposed an adaptive genetic algorithm was tested in terms of the solution accuracy and algorithm speed during numerical experiments. We found that our algorithm can generate the optimal solution within a reasonable computational time.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.1-7
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• 2012

This paper deals with the global path planning problem for AUVs (autonomous underwater vehicles) in a tidal current field. The previous researches in the field were unsuccessful at simultaneously addressing the two issues of obstacle avoidance and tidal current-based optimization. The use of a genetic algorithm is proposed in this paper to move past this limitation and solve both issues at once. Simulation results showed that the genetic algorithm could be applied to generate an optimal path in the field of a tidal current with multiple obstacles.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.231-233
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• 2007

구조개편 이후 전력수급계획 수립여건이 한전의 독점적 계책에서 사업자 건설의향으로 전환됨에 따라 신규설비 건설계획은 수익성 위주로 전환되었다. 이에 따라 본 논문에서는 기저선비(원자력, 석탄화력) 운전효율성 항상 차원에서 건설되던 양수설비의 적정 설비규모를 계통 공급신뢰도 측면, 에너지 이응 효율성 향상 측면, 전력시장에서의 경제성 측면에서 검토하여 최적전원구성(Best Fuel Mix) 유도론 위한 정책적 방향을 제시하였다.