• Korean Management Science Review
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• v.25 no.2
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• pp.73-80
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• 2008

The location area planning is to assign cells to the location areas of a wireless communication network in an optimum manner. The two important cost components are cost of location update and cost of paging that are of conflicting in nature; i.e., minimizing the registration cost might increase the search cost. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. In fact this is shown to be an NP-complete problem in an earlier study. In this paper, we use an ant colony optimization method to obtain the best/optimal group of cells for a given a network.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.19-27
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• 1997

This paper presents rough cut tool path planning for the fewer-axis machine consisting of a three-axis CNC machine and a rotary indexing table. In the problem dealt with in this paper, the tool orientation is "intermediately" changed, distinguished from the conventional problem where the tool orientation is assumed to be fixed. The developed rough cut path planning algorithm tries to minimize the number of tool orientation (setup) changes together with tool changes and the machining time for the rough cut by the four procedures: a) decomposition of the machining area based on the possibility of tool interference (via convex hull operation), b) determination of the optimal tool size and orientation (via network graph theory and branch-and bound algorithm), c) generation of tool path for the tool and orientation (based on zig-zag pattern), and d) feedrate adjustment to maintain the cutting force at an operation level (based on average cutting force). The developed algorithms are validated via computer simulations, and can be also used in pure fiveaxis machining environment without modification.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.171-179
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• 2010

A fundamental technology of UGV(Unmanned Ground Vehicle) to perform a given mission with success in various environment is a path planning method which generates a safe and optimal path to the goal. In this paper, we suggest a local path-planning method of UGV based on the binary map using world model data which is gathered from terrain perception sensors. In specially, we present three core algorithms such as shortest path computation algorithm, path optimization algorithm and path smoothing algorithm those are used in the each composition module of LPP component. A simulation is conducted with M&S(Modeling & Simulation) system in order to verify the performance of each core algorithm and the performance of LPP component with scenarios.

• Journal of Environmental Science International
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• v.23 no.7
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• pp.1213-1221
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• 2014

In the background of rapid urbanization and frequent earthquakes, earthquake disaster prevention planning has become an important topic of current research. Universities are irreplaceable disaster shelter, as they are public institutions with a lot of open space. This article puts forward the concept of "disaster prevention campus". With the refuge behavioral and psychological characteristics of people in the campus when the earthquake happens, it integrated uses GIS spatial analysis technique, takes Shandong Agricultural University as an example, and studies the spatial pattern of earthquake disaster prevention planning in campus from five aspects. The aspects include building distribution, population distribution, analysis of service radius, infrastructure configuration and choice of the optimal refuge path. On the basis of researches above, reform proposals and specific strategies are put forward to build the safe and harmonious disaster prevention campus.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.972-976
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• 2015

The objective of this research is to verify the quantitative efficiency of a bimanual robotic task. Bimanual robots can realize dexterous and complicated motions using two cooperating arms. However, its motion planning and control method are not simple for implementing flexible tasks such as assembly. In this paper, the proposed motion planning method is used to find an optimal solution satisfying a designed cost function and constraints with regard to the kinematics and redundancy of the bimanual robot. The simulation results show that the lifetime of the manipulator can be changed by the proposed cost function consisting of angular velocity and angular acceleration of each joint in the same assembly task.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.203-209
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• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.164-164
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work environment without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for global and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.444-449
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• 2006

Path planning is a key element in navigation of a mobile robot. Several algorithms such as a gradient method have been successfully implemented so for. Although the gradient method can provide the global optimal path, it computes the navigation function over the whole environment at all times, which result in high computational cost. This paper proposes a high-speed path planning scheme, called a gradient method with topological information, in which the search space for computation of a navigation function can be remarkably reduced by exploiting the characteristics of the topological information reflecting the topology of the navigation path. The computing time of the gradient method with topological information can therefore be significantly decreased without losing the global optimality. This reduced path update period allows the mobile robot to find a collision-free path even in the dynamic environment.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.323-341
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• 1997

Traditionally, the Process Planning problems and the Scheduling problems have been considered as independent ones. However, we can take much advantages by solving the two problems simultaneously. In this paper, we deal with the enlarged problem that takes into account both the process planning and the scheduling problems. And we present a solution algorithm for the problem assuming that the given process plan data is represented by AND/OR graph. A mathematical model(mixed ILP model) whose objective is the minimization of the makespan, is formulated. We found that we can get the optimal solutions of the small-size problems within reasonable time limits, but not the large-size problems. So we devised an algorithm based on the decomposition strategy to solve the large-scale problems (realistic problems) within practical time limits.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.8-14
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• 2007

This paper addresses the allocation planning of the storage location in a warehouse system that the dedicated storage method is used. In the discrete finite time period model, the demands for storage location of products are dynamic for time periods. The planning is to determine the reallocation time period and the storage location of the products in reallocation time period, which minimizes costs. The cost factors are the reallocation cost, the travel cost within warehouse and the surplus storage location cost. A model is formulated, and the property of optimal solution is characterized. The dynamic programming algorithm is developed, and a numerical example is shown.