• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.115-122
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• 2014

Mobile robot has been studied for long time due to its simple structure and easy modeling. Regarding path planning of the mobile robot, we suggest real-time hybrid path planning algorithm which is the combination of optimal path planning and real-time path planning in this paper. Real-time hybrid path planning algorithm modifies, finds best route, and saves calculating time. It firstly plan the route with real-time path planning then robot starts to move according to the planned route. While robot is moving, update the route as the best outcome which found by optimal path planning algorithm. Verifying the performance of the proposed method through the comparing real-time hybrid path planning with optimal path planning will be done.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.62-69
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• 2005

The optimal design of transmission system expansion planning is an important part of the overall planning task of electric power system under competitive electricity market environments. One of main keys of the successful grid expansion planning comes from optimal reliability level/criteria decision, which should be given for constraint in the optimal expansion problem. However, it's very difficult to decide logically the optimal reliability criteria of a transmission system as well as generation system expansion planning in a society. This paper approaches a methodology for deciding the optimal reliability criteria for an optimal transmission system expansion planning. A deterministic reliability criteria, BRR (Bus Reserve Rate) is used in this study. The optimal reliability criteria, BRR/sup */, is decided at minimum cost point of total cost curve which is the sum of the utility cost associated with construction cost and the customer outage cost associated with supply interruptions for load considering bus reserve rate at load buses in long term forecasting. The characteristics and effectiveness of this methodology are illustrated by the case study using IEEE-RTS.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.301-303
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• 2005

This paper presents long-term shunt capacitor planning using optimal power flow. OPF allows the planning engineer to find feasible solution with minimal amount of engineering time. We used OPF for Shunt capacitor planning to get an optimal solution. The result of OPF is compared to the analysis by the conventional loadflow method and it is proved that OPF gives more cheaper and better planning solution. With the result, we analyzed the operational perspective for the reactive power supply and demand.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.21-27
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• 2010

This paper examines the long-run social welfare maximization problems facing public utilities, which includes consideration of the cost of capital or other fixed costs of production, from which it derives optimal investment decisions in a reliability differentiated pricing based market. Reliability differentiated pricing policies lead to straightforward mathematical results on optimal investment decisions in generation and transmission expansion planning. This paper presents the mathematical conditions for optimal investment decisions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.27-34
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• 2017

Highly informative admissible heuristics can help to conduct more efficient search for optimal solutions. However, in general, more informative ones of heuristics from planning problems requires lots of computational effort. To address this problem, we propose an Delete Relaxation based Action Costs-based Planning Graph(ACPG) and Action Costs-based Heuristics for solving optimal planning problems more efficiently. The ACPG is an extended one to be applied to can find action costs between subgoal & goal conditions from the Relaxed Planning Graph(RPG) which is a common means to get heuristics for solving the planning problems, Action Costs-based Heuristics utilizing ACPG can find action costs difference between subgoal & goal conditions in an effective way, and then consider them to estimate the goal distance. In this paper, we present the heuristics algorithm to compute Action Costs-based Heuristics, and then explain experimental analysis to investigate the efficiency and the accuracy of the Action Costs-based Heuristics.

• Journal of Astronomy and Space Sciences
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• v.21 no.3
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• pp.209-220
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• 2004

Some methods have been presented to get optimal formation trajectories in the step of configuration or reconfiguration, which subject to constraints of collision avoidance and final configuration. In this study, a method for optimal formation trajectory-planning is introduced in view of fuel/time minimization using parameter optimization technique which has not been applied to optimal trajectory-planning for satellite formation flying. New constraints of nonlinear equality are derived for final configuration and constraints of nonlinear inequality are used for collision avoidance. The final configuration constraints are that three or more satellites should be placed in an equilateral polygon of the circular horizontal plane orbit. Several examples are given to get optimal trajectories based on the parameter optimization problem which subjects to constraints of collision avoidance and final configuration. They show that the introduced method for trajectory-planning is well suited to trajectory design problems of formation flying missions.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.1003-1012
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• 2000

When a robot hand grasp an object, the number of ways to grasp it stably are infinite and thus an optimal grasp planning is needed to find the optimal grasp points for satisfying the objective of the given task. In this paper, we first define some grasp indices to evaluate the quality of each feasible grasp and then a weighted composite grasp index by combining all of the grasp indices is also defined. Next, we propose a method to find the optimal grasp points of the given object by comparing the defined weighted composite grasp index for each feasible grasp points. By simulation results, we show the effectiveness of the proposed optimal grasp planning method and also discuss the trend of each grasp index as the grasp polygon.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.255-255
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• 2000

Technical advance of electrical chart and cruising equipment make it possible to sail without a man. It is important to decide the cruising route in view of effectiveness and stability of a ship. So we need to study on the optimal trajectory planning. Genetic algorithm is a strong optimization algorithm with adaptational random search. It is a good choice to apply genetic algorithm to the trajectory planning of a ship. We modify a genetic algorithm to solve this problem. The effectiveness of the revised genetic algorithm is assured through computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.407-411
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• 1992

A method for optimal route planning is presented with the assumption that the overall defended area is known in terms of threat potential function. This approach employes tangent plane to reduce the dimension of the state space for optimal programming problems with a state equality constraint. One-dimensional search algorithm is used to select the optimal route among the extermal fields which are obtained by integrating three differential equations from the initial values. In addition to being useful for the route planning through threat potential area, the trajectory planning will be suitable for general two-dimensional searching problems.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.66-74
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• 2023

With the increase of interest in developing Maritime Autonomous Surface Ships (MASS), an optimal ship route planning is gradually gaining popularity as one of the important subsystems for autonomy of modern marine vessels. In the present paper, an optimal ship route planning model for MASS is proposed using a nonlinear MPC approach together with a nonlinear MMG model. Results drawn from this study demonstrated that the optimization problem for the ship route was successfully solved with satisfaction of the nonlinear dynamics of the ship and all constraints for the state and manipulated variables using the nonlinear MPC approach. Given that a route generation system capable of accounting for nonlinear dynamics of the ship and equality/inequality constraints is essential for achieving fully autonomous navigation at sea, it is expected that this paper will contribute to the field of autonomous vehicles by demonstrating the performance of the proposed optimal ship route planning model.