• ETRI Journal
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• 제44권4호
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• pp.641-653
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• 2022

In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane-change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane-change trajectories for autonomous vehicles. When comparing this generated trajectory with a man-generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane-change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane-change trajectory.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.1307-1311
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• 2004

This paper deals with an automated computer-aided process planning and die design system by which designer can determine operation sequences even if they have a little experience in process planning and die design for axisymmetric products. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM softwares, DEFORM and ANSYS, to form a useful package. They can provide a flexible process based on either the reduction in the number of forming sequences by combining the possible two processes in sequence, or the reduction of deviation of the distribution on the level of the required forming loads by controlling the forming ratios. Especially in die design module an optimal design technique and horizontal split die were investigated for determining appropriate dimensions of components of multi-former die set. It is constructed that the proposed method can be beneficial for improving the tool life of die set at practice.

• 대한전기학회논문지
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• 제34권8호
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• pp.308-316
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• 1985

This paper proposes an analytic tool for long-term generation expansion planning based on the maximum principle. Many research works have been performed in the field of generation expansion planning. But few works can be found with the maxinmum principle. A recently published one worked by professor Young Moon Park et al. shows remarkable improvements in modeling and computation. But this modeling allows only thermal units. This paper has extended Professor Park's model so that the optimal pumped-storage operation is taken into account. So the ability for practical application is enhanced. In addition, the analytic supply-shortage cost function is included. The maximum principle is solved by gradient search due to its simplicity. Every iteration is treated as if mathematical programming such that all controls from the initial to the terminal time are manipulated within the same plane. Proposed methodology is tested in a real scale power system and the simulation results are compared with other available package. Capability of proposed method is fully demonstrated. It is expected that the proposed method can be served as a powerful analytic tool for long-term generation expansion planning.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.698-702
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• 1992

In this paper, Micro-Genetic algorithms(.mu.-GAs) is proposed on a minimum-time path planning for robot manipulator, which is a kind of optimization algorithm. 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 computation burden and can't often find the optimal values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimal values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• 로봇학회논문지
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• 제2권2호
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• pp.183-190
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• 2007

The most important thing for navigation of a mobile robot is to find the most suitable path and avoid the obstacles in the static and dynamic environment. This paper presents a method to search the optimal path in start space extended to time domain with considering a velocity and a direction of moving obstacles. A modified version of $A^*$ algorithm has been applied for path planning in this work and proposed a method of path search to avoid a collision with moving obstacle in space-tim domain with a velocity and an orientation of obstacles. The velocity and the direction for moving obstacle are assumed as linear form. The simulation result shows that a mobile robot navigates safely among moving obstacles of constant linear velocity. This work can be applied for not only a moving robot but also a legged humanoid robot and all fields where the path planning is required.

• Journal of Electrical Engineering and information Science
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• 제2권3호
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• pp.51-60
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• 1997

A practically applicable collision free trajectory planning technique for tow robot systems is proposed. The robot trajectories considered in this work are composed of many segments, an at the intersection points between segments robots stop to assemble, weld, ordo other jobs by the attached a end-effectors. The proposed method is based on the Planning-Coordination Decomposition where planning is to find a trajectory of each robot independently according to their tasks and coordination is to find a velocity modification profile to avoid collision with each other. To fully utilize the independently planned trajectories and to ensure no geometrical path deviation after coordination, we develop a simple technique added the minimal delay time to avoid collision just before moving along path segments. We determine the least delay time by the graphical method in the Coordination space where collisions and coordinations are easily visualized. We classify all possible cases into 3 group and derive the optimal solution for each group.

• 대한전기학회논문지:전력기술부문A
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• 제50권2호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.715-718
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• 1998

There are a lot of paths which connect between the mobile robot and the goat point. To make a mobile robot arrive at the goal point fastly, The optimal path is needed and a path palnning is necessary. In this paper, we propose a new method of path planning to find a path for mobile robot. It is based on Ginetic Algorithm for serching the optimal grobal path planning. Simulations show the efficiency for the grobal path planning.

• 대한전기학회논문지:전력기술부문A
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• 제49권11호
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• pp.566-574
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• 2000

This paper propose a heuristic algorithm based on the Branch-Exchange (BE) method to solve Optimal feeder Routing(OFR) problem for the distribution system planning. The cost function of the OFR problem is consisted of the investment cost representing the feeder installation and the system operation cost representing the system power loss. We propose a properly designed heuristic strategy, which can handle the horizon-year expansion planning problem of power distribution network. We also used the loop selection method which can define the maximum loss reduction in the network to reduce calculation time, and proposed a new index of power loss which is designed to estimate the power loss reduction in the BE. The proposed index, can be considered with both sides, the low voltage side and voltage side branch connected with tie one. The performances of the proposed algorithms and loss index were shown with 32, 69 example bus system.

• 대한안전경영과학회지
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• 제12권2호
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• pp.17-23
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• 2010

The large-scale disasters occur to unexpected accidents such as natural disasters(earthquake, typhoon, tsunami, etc.), and human-caused accidents(fire, collapse, terror etc.). Rescue teams perform rescue activities to save many lives in large-scale disaster area. The main purpose of this study is to compose a optimal routing planning for rescue of multiple victims in disaster area. A realistic routing planning with rescue limit time which considers rehabilitation and reconstruction will be suggested in this study. A mathematical programming model and a hybrid genetic algorithm will be suggested to minimize the total spending time. By comparing the result, the suggested algorithm gives a better solution than existing algorithms.