• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1876-1885
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• 2003

The artificial potential field (APF) methods provide simple and efficient motion planners for practical purposes. However, these methods have a local minimum problem, which can trap an object before reaching its goal. The local minimum problem is sometimes inevitable when an object moves in unknown environments, because the object cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planing. In this study, we propose a new concept using a virtual obstacle to escape local minima that occur in local path planning. A virtual obstacle is located around local minima to repel an object from local minima. We also propose the discrete modeling method for the modeling of arbitrary shaped objects used in this approach. This modeling method is adaptable for real-time path planning because it is reliable and provides lower complexity.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1061-1064
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• 2009

The objective of this study is to find the optimal operational planning of the hybrid cooling system, which is combined by ice storage system and the absorption chiller. The optimization technique used in this study is dynamic programming. The objective function is summed cost during a day including charge and discharge periods of ice storage system and operation time of absorption chiller. Assuming that initially ice storage tank is stored fully and the cooling load is perfectly predicted for the operational planning. This method provides the most efficient and economic combination of equipment operational planning for cooling with respect to energy consumption cost.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.485-491
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• 1990

We propose a minimum-time path planning soheme for the robot manipulator using Hopfield neural network. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural network technique, which can allow the parallel computation, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using the PUMA 560 manipulator.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.10
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• pp.805-810
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• 1989

This paper presents a method for planning reactive power compensation such as shunt capacitors and reacters so as to maintain bus voltage in acceptable range during steady state operation in power system. The algorithm in this paper decomposes the problem into reactive power planning module for the compensation of bus voltage and load flow module for adjusting the error resulted from the linear approximation. A planning technique is based on linear programming to minimize the amount of added reactive power compensation in each case. Transformer tap settings and generator voltages are adjusted to minimize the compensation. The constraints are the operation limits of the control variables and bus voltages. The result of one sample system is presented to confirm the practical use of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.58-66
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• 2001

This paper presents an application of a newly designed Adaptive Genetic Algorithm (AGA) to solve the Optimal Feeder Routing (OFR) problem for distribution system planning. The main objective of the OFR problem usually is to minimize the total cost that is the sum of investment costs and system operation costs. We propose a properly designed AGA, in this paper, which can handle the horizon-year expansion planning problem of power distribution network in which the location of substation candidates, the location and amount of forecasted demands are given. In the proposed AGA, we applied adaptive operators using specially designed adaptive probabilities. we also a Simplified Load Flow (SLF) technique for radial networks to improve a searching efficiency of AGA. The proposed algorithm has been evaluated with the practical 32, 69 bus test system to show favorable performance. It is also shown that the proposed method for the OFR can also be used for the network reconfiguration problem in distribution system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1364-1371
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• 1990

We propose a time-optimal path planning scheme for the robot manipulator using Hopfield neural network. The time-optimal path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural networke technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using a PUMA 560 manipulator.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.51-56
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• 2005

The objective of this study is to develop Home Indoor Air Quality evaluation prorgram considering planning and construction stage for architects, engineers and occupants to estimate and improve the IAQ of a home. In this study, the IAQ modeling technique was discussed to determine the appropriate modeling of housing unit in Korea. The program algorithm was developed based on the selected model reflecting planning and construction stage. This program can be applied to estimate the IAQ of a home and encourage appropriate action in advance.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.107-116
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• 2006

We propose a planning algorithm to automatically generate a robust behavior plan (RBP) with which mobile robots can achieve their task goal from any initial states under dynamically changing environments. For this, task description space (TDS) is formulated, where a redundant task configuration space and simulation model of physical space are employed. Successful task episodes are collected, where $A^*$ algorithm is employed. Interesting TDS state vectors are extracted, where occurrence frequency is used. Clusters of TDS state vectors are found by using state transition tuples and features of state transition tuples. From these operations, characteristics of successfully performed tasks by a simulator are abstracted and generalized. Then, a robust behavior plan is constructed as an ordered tree structure, where nodes of the tree are represented by attentive TDS state vector of each cluster. The validity of our method is tested by real robot's experimentation for a box-pushing-into-a-goal task.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2315-2317
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• 1998

There has been extensive efforts about robot path planning. Some major approaches are the roadmap approach, potential field approach and the cell decomposition approach. However, most of the path planning methods proposed so far based on above approaches consider the terrains filled with binary obstacles, i.e., if there exists an obstacle, robot simply cannot pass the location. In this paper, A mobile robot path planning method based on the cell decomposition technique for mobile robot that takes account of the terrain with varing degrees of travers-ability is discussed.

• Journal of The Korea Institute of Healthcare Architecture
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• v.10 no.2
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• pp.71-82
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• 2004

The purpose of this study is to analyze the wind velocity ratio in respect of layout types of housing in multi-family housing. The wind velocity ratio is a difference of wind velocity between on the leeward and on the windward side of multi-family housing. The layout types of housing are grid layout pattern of linear type, mixture pattern of Linear type + tower type and layout pattern of tower type. The planning of wind flow is an induced technique to increase in wind velocity in the city and multi-family housing. This study investigates wind velocity ratio into layout types of housing. consequently, analysis were basic design data for the planning techique of wind flow suggested.