• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.4-5
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• 2014

Planning earthmoving haul-route must be preceded for appropriate equipment fleet assignment. However, traditional haul-route planning methods have limitations relative to practical usage because multiple variables (e.g., grade/rolling resistance, length, equipment's weight etc.) should be considered at a time. Genetic algorithm(GA) was introduced to improve these traditional methods. However, GA based haul-route planning method still remains in inefficiency relative to computation performance. This study presents a new haul-route searching method that computes an optimal haul-route using GA. The system prototype is developed by using MATLAB(ver. 2008b). The system identifies an optimal haul-route by considering equipment type, soil type, and soil condition.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.96-99
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• 1990

Recently, electric energy consumption pattern shows very high peak load with low load factor. This Load pattern have made electric utilities be interested in Load Management, many studies are reported. But most of these studies are concerned with Rate - Load shape relation, a few of these are concerned with generating cost reduction. In this study, the effect of Load Management is incorporated to establish optimal Generation Expansion Planning. Using avoided cost, optimal generation expansion planning is achieved to make maximum avoided cost of Electric utility. Dynamic programming technique is used to solve this algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.1
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• pp.9-17
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• 1992

Proper resource allocation is also a very important topic in power system problems, especially in operation and planning. One such is optimal maintenance problem in operation and planning. Least cost and highest reliability should be the subjects to be pursued. A probabilistic operation simulation model developed recently by authors is applied to the proboem of optimal maintenance scheduling. Three different methods are compared, marginal maintenance cost, levelized risk and maintenance space. The method by the marginal maintenance costs shows the least cost, the highest reliability and the highest maintenance outage rates. This latter characteristics may considerably influence the results of genetation planning, because the usual maintenance outages obtained from the other methods have shown to be lower.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.696-702
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• 2004

An optimal trajectory generation algorithm for capturing a moving object by a mobile robot in real-time is proposed in this paper. The linear and rotational velocities of the moving object are estimated using the Kalman filter, as a state estimator. For the estimation, the moving object is tracked by a 2-DOF active camera mounted on the mobile robot, which enables a mobile manipulator to track the mobile robot until the capturing moment. The optimal trajectory for capturing the moving object is dependent on the initial conditions of the mobile robot as well as the moving object. Therefore, real-time trajectory planning for the mobile robot is definitely required for the successful capturing of the moving object. The performance of proposed algorithm is verified through the real experiments and the superiority is demonstrated by comparing to other algorithms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.176-181
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• 2000

Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

• Progress in Medical Physics
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• v.1 no.1
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• pp.23-29
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• 1990

In order to explane the stereotactic procedure, the three steps of the procedure (target localization, dose planning, and radiation treatment) must be examined separately. The ultimate accuracy of the full procedure is dependent on each of these steps and on the consistancy of the approach The concern in this article was about dose planning, which is a important factor to the success of radiation treatment. The major factor in dose planning is a dosimetry system to evaluate the dose delivered to the target and normal tissues in the patient, while it generates an optimal dose distribution that will satisfy a set of clinical criteria for the patient. A three-dimensional treatment planning program is a prerequisite for treatment plan optimization. It must cover 3-D methods for representing the patient, the dose distributions, and beam settings. The major problems and possible modelings about 3-D factors and optimization technique were discussed to simplify and solve the problems associatied with 3-D optimization, with relative ease and efficiency. These modification can simplify the optimization problem while saving time, and can be used to develop reference dose planning system to prepare standard guideline for the selection of optimum beam parameters, such as the target position, collimator size, arc spacing, the variation in arc length and weight. The method yields good results which can then be simulated and tailored to the individual case. The procedure needed for dose planning in stereotactic radiosurgery is shown in figure 1.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.192-198
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• 2016

Motion planning problem is still one of the important issues in robotic applications. In many real-time motion planning problems, it is advisable to find a feasible solution quickly and improve the found solution toward the optimal one before the previously-arranged motion plan ends. For such reasons, sampling-based approaches are becoming popular for real-time application. Especially the use of a rapidly exploring random $tree^*$ ($RRT^*$) algorithm is attractive in real-time application, because it is possible to approach an optimal solution by iterating itself. This paper presents a modified version of informed $RRT^*$ which is an extended version of $RRT^*$ to increase the rate of convergence to optimal solution by improving the sampling method of $RRT^*$. In online motion planning, the robot plans a path while simultaneously moving along the planned path. Therefore, the part of the path near the robot is less likely to be sampled extensively. For a better solution in online motion planning, we modified the sampling method of informed $RRT^*$ by combining with the sampling method to improve the path nearby robot. With comparison among basic $RRT^*$, informed $RRT^*$ and the proposed $RRT^*$ in online motion planning, the proposed $RRT^*$ showed the best result by representing the closest solution to optimum.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.298-306
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• 2013

Nowadays, a transporter manager plans the schedule of the block transportation by considering the experience of the manager, the production process of the blocks and the priority of the block transportation in shipyard. The schedule planning of the block transportation should be rearranged for the reflection of the path blocking cases occurred by unexpected obstacles or delays in transportation. In this paper, the optimal block transportation path planning system is developed for rearranging the schedule of the block transportation by considering the damaged path. $A^*$ algorithm is applied to calculate the new shortest path between the departure and arrival of the blocks transported through the damaged path. In this algorithm, the first node of the damaged path is considered as the starting position of the new shortest path, and then the shortest path calculation is completed if the new shortest path is connected to the one of nodes in the original path. In addition, the data structure for the algorithm is designed. This optimal block transportation path planning system is applied to the Philippine Subic shipyard and the ability of the rapid path modification is verified.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.35-44
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• 2012

This paper presents a method to optimize motion planning for industrial manipulators with redundancy. For optimal motion planning, first of all, particular inverse kinematic solution is needed to improve efficiency for manipulators with redundancy working in various environments. In this paper, we propose three kinds of methods for solving inverse kinematics problems; numerical and combined approach. Also, we introduce methods for optimal motion planning using potential function considering the order of priority. For efficient movement in industrial settings, this paper presents methods to plan motions by considering colliding obstacles, joint limits, and interference between whole arms. To confirm improved performance of robot applying the proposed algorithms, we use two kinds of robots with redundancy. One is a single arm robot with 7DOF and another is a dual arm robot with 15DOF which consists of left arm, right arm with each 7DOF, and a torso part with 1DOF. The proposed algorithms are verified through several numerical examples as well as by real implementation in robot controllers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.240-257
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• 2006

In an effort to gain competitiveness, recently many companies are trying to outsource their logistics activities to the logistics specialists, while concentrating on their core and strategic business area. Because of this trend, the third party logistics comes to the fore, catching people's attention, and expanding its market rapidly. Under these circumstances, the third party logistics companies are making every effort to improve their logistics services and to develop an information system in order to enhance their competitiveness. In particular, among these efforts one of the critical parts is the decision support system for effective transportation network planning. To this end, this study has developed an efficient decision support system for an optimal transportation network planning by comprehensively considering the transportation mode, routing, assignment, and schedule. As a result of this study, the new system enables the expansion of the third party logistics companies' services including the multimodal transportation, not to mention one mode of transportation, and also gets them ready to plan an international transportation network.