• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.823-825
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• 1995

This paper presents an efficient and robust robot path planning technique that can always find a path, if one exists, in a densely cluttered, unknown and unstructured obstacle environment. The terrain in which the robot is expected to navigate is represented as a tesselated grid of square cells. The generated path is resolution complete and also resolution optimal once the terrain is fully explored by the robot or all the information about the terrain is given. The technique enables the accurate wave propagation to the diagonally adjacent cells and facilitates the implementations of various essential features for a real-time path planner such as partial updates and parallel computations.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.8
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• pp.73-82
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• 2004

In this paper, implementation of obstacle avoidance of a nonholonomic mobile robot in unstructured environment is introduced. To avoid obstacles, first, a reference collision-free path for the MR is generated off-line using HJB-based optimal path planning method. A controller is designed using integrator backstepping method for tracking the generated reference path. To implement the designed controller, a control system are needed and composed of camera system and PIC-based controller. The workspace is observed by a ceiling-mounted USB camera as part of an un-calibrated camera system. Thus the positional information of the MR is updated frequently and the MR can get the useful inputs for its tracking controller. The whole control system is realized by integrating a computer with PIC-based microprocessor using wireless communication: the image processing control module and path planning module serve as high level computer control while the device control serves as low level PIC microprocessor control. The simulation and experimental results show the effectiveness of the designed control system.

• Journal of Distribution Science
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• v.13 no.6
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• pp.11-15
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• 2015

Purpose - Robot path planning, a constrained optimization problem, has been an active research area with many methods developed to tackle it. This study proposes the use of a Rapidly-exploring Random Tree and Particle Swarm Optimizer algorithm for path planning. Research design, data, and methodology - The grid method is built to describe the working space of the mobile robot, then the Rapidly-exploring Random Tree algorithm is applied to obtain the global navigation path and the Particle Swarm Optimizer algorithm is adopted to obtain the best path. Results - Computer experiment results demonstrate that this novel algorithm can rapidly plan an optimal path in a cluttered environment. Successful obstacle avoidance is achieved, the model is robust, and performs reliably. The effectiveness and efficiency of the proposed algorithm is demonstrated through simulation studies. Conclusions - The findings could provide insights to the validity and practicability of the method. This method makes it is easy to build a model and meet real-time demand for mobile robot navigation with a simple algorithm, which results in a certain practical value for distribution environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1260-1272
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• 2008

This paper proposes object detection algorithm using laser scanner and vision system for the path planning of autonomous mobile agents. As the scanner-based method can observe the obstacles in only two dimensions, it is hard to detect the shape and the number of obstacles. On the other hand, vision-based method is sensitive to the environment and has its difficulty in the accurate distance measurement. Thus, we combine these two methods based on K-means algorithm such that the obstacle avoidance and optimal path planning of autonomous mobile agents can be achieved.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.333-334
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• 2007

We propose a path planning method to decrease a inspection lead time of line scan camera in SMT(surface mount technology) in-line system. The inspection window area of printed circuit board should be minimized to consider the FOV(field of view) of line scan camera so that line scan inspector is going to find a optimal solution of path planning. We propose one of the hierarchical clustrering algorithm for a given board. Comparative simulation results are presented to verify the usefulness of proposed method.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.1-7
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• 2024

The utilization of Unmanned Aerial Vehicles (UAVs) is expanding in various industries such as logistics, manufacturing, and transportation. However, to operate a large number of UAVs, it is imperative to first plan a secure and efficient self-configuring communication network for UAVs. In this study, we proposed a method for planning a secure and efficient UAV self-configuring communication network using Voronoi diagrams in the following three steps: 1) generating Voronoi diagrams using obstacles, 2) selecting obstacles to consider for path generation, and 3) planning the optimal path and outputting the path. The real-time feasibility of using the proposed method for planning optimal communication paths for a realistic number of UAVs was experimentally validated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1651-1654
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• 2003

The process equipment for handling high level radioactive materials, such as spent nuclear fuel, is operated within a sealed facility, called a hot cell, due to high radioactivity. Thus, this equipment should be maintained and repaired by remotely operated manipulator. In this study, to carry out the sale and effective maintenance of the process equipment installed in the hot cell by a servo type manipulator, a collision free motion planning method of the manipulator using virtual prototyping technology is suggested. To do this, the parts are modelled in 3-D graphics, assembled, and kinematics are assigned and the virtual workcell is implemented in the graphical environment which is the same as the real environment. The method proposed in this paper is to find the optimal path of the manipulator using the function of the collision detection in the graphic simulator. The proposed path planning method and this graphic simulator of manipulator can be effectively used in designing of the maintenance processes for the hot cell equipment and enhancing the reliability of the spent fuel management.

• Journal of the military operations research society of Korea
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• v.36 no.3
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• pp.135-145
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• 2010

The submarine is very threatening and secretive weapon system that achieves missions under the sea. However, the submarine is faced with danger that can be attacked from the enemy when is detected by sensor or rose to the surface. This study will be planned optimal path to maximize the survival rate that considers submarine navigation capability in underwater and search activity of hostile warships. A mathematical programming model and a heuristic algorithm will be suggested in this study. The mathematical programming model is verified by using ILOG CPLEX. The submarine path, unit time(distance) of navigation, survival rate, and computation time is computed by using a heuristic algorithm.

• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.252-259
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• 1998

Vehicle navigation systems employ a certain route planning algorithm that provides the shortest path between the starting point and the destination point. The performance of a given route planning algorithm is measured through the degree of optimal route selection and the time cost to complete searching an optimal path. In this paper, various route planning algorithms are evaluated through computer simulation based on a real digital map database. Among those algorithms evaluated in this paper, the Modified Bi-directional A${\ast}$ algorithm is found to be the best algorithm for use in vehicle navigation systems.