• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.279-282
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• 1996

Collision avoidance is a method to direct a mobile robot without collision when traversing the environment. This kind of navigation is to reach a destination without getting lost. In this paper, we use a genetic algorithm for the path planning and collision avoidance. Genetic algorithm searches for path in the entire, continuous free space and unifies global path planning and local path planning. It is a efficient and effective method when compared with traditional collision avoidance algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.8
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• pp.437-444
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• 2014

In this paper, we propose a path loss model with the multiple antennas and doppler shift for high speed railroad communication. Path loss model is very important in order to design consider diverse characteristic in high-speed train communication. Currently wireless communication systems use the multiple antennas in order to improve the channel capacity or diversity gain. However, until recently, many researches on path loss model only consider geographical environment between the transmitter and the receiver. There is no study about path loss model considering diversity effect and doppler shift. In order to make average residuals considering doppler shift we use tuned free space path loss model which is utilized for measurement results at high speed railroad. The environment of high speed rail is mostly at viaduct and flatland over than 50 percent. And in order to make average residuals considering multiple antenna we use theoretical estimation of diversity gain with MRC scheme. proposed model predict loss of received signal by estimating average residuals between diversity effect and doppler shift.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.2
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• pp.121-128
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• 2021

In this paper, we propose a path generation and tracking algorithm of an unmanned air vehicle in a two-dimensional plane given the initial and final points. The path generation algorithm using the Dubins curve proposed in this work has the advantage that it can be applied in real time to an unmanned air vehicle. The path tracking algorithm is an algorithm similar to the line-of-sight induction algorithm. In order to efficiently control the direction angle, a gain related to the look ahead distance concept is introduced. Most of UAVs have the limited maximum curvature due to the structural constraints. A numerical simulation is conducted to follow the path generated by the sliding mode controller considering the angular velocity limit. The path generation and tracking performance is verified by comparing the suggested controller with conventional control techniques.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.763-770
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• 2022

In an environment where multiple drones are operated, collisions can occur when path points overlap, and collision avoidance in preparation for this is essential. When multiple drones perform multiple tasks, it is not appropriate to use a method to generate a collision-avoiding path in the path planning phase because the path of the drone is complex and there are too many collision prediction points. In this paper, we generate a path through a commonly used path generation algorithm and propose a collision avoidance method using speed profile optimization from that path segment. The safe distance between drones was considered at the expected point of collision between paths of drones, and it was designed to assign a speed profile to the path segment. The optimization problem was defined by setting the distance between drones as variables in the flight time equation. We constructed the constraints through linearize and convexification, and compared the computation time of SQP and convex optimization method in multiple drone operating environments. Finally, we confirmed whether the results of performing convex optimization in the 20 drone operating environments were suitable for the multiple drone operating system proposed in this study.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1014-1020
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• 1990

Iterative algorithms for detecting the collision of convex objects whose motion is characterized by a path in configuration space are described. They use as an essential substep the computation of the distance between the two objects. When the objects are polytopes in either two or three dimensional space, an algorithm is given which terminates in a finite number of iterations. It determines either that no collision occurs or the first collision point on the path. Extensive numerical experiments for practical problems show that the computational time is short and grows only linearly in the total number of vertices of the two polytopes.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.329-338
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• 1994

This paper presents a novel method of path planning for a quadruped walking robot on irregular terrain. In the previous study on the path planning problem of mobile robots, it has been usually focused on the collision-free path planning for wheeled robots. The path planning problem of legged roboth, however, has unique aspects from the point of viw that the legged robot can cross over the obstacles and the gait constraint should be considered in the process of planning a path. To resolve this unique problem systematically, a new concept of the artificial intensity field of light is numerically constructed over the configuration space of the robot including the transformed obstacles and a feasible path is sought in the field. Also, the efficiency of the proposed method is shown by various simulation results.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.629-634
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• 1995

The purpose of this paper is to develop a method of Collision-Free Path Planning (CFPP) for an articulated robot. First, the configuration of the robot is formed by a set of robot joint angles derived fromm robot inverse kinematics. The joint space that is made of the joint angle set, forms a Configuration space (Cspace). Obstacles in the robot workcell are also transformed and mapped into the Cspace, which makes Cobstacles in the Cspace. (The Cobstacles represented in the Cspace is actually the configurations of the robot causing collision.) Secondly, a connected graph, a kind of roadmap, is constructed from the free configurations in the 3 dimensional Cspace, where the configurations are randomly sampled form the free Cspace. Thirdly, robot paths are optimally in order to minimize of the sum of joint angle movements. A path searching algorithm based on A is employed in determining the paths. Finally, the whole procedures for the CFPP method are illustrated with a 3 axis articulated robot. The main characteristics of the method are; 1) it deals with CFPP for an articulated robot in a 3-dimensional workcell, 2) it guarantees finding a collision free path, if such a path exists, 3) it provides distance optimization in terms of joint angle movements. The whole procedures are implemented by C on an IBM compatible 486 PC. GL (Graphic Library) on an IRIS CAD workstation is utilized to produce fine graphic outputs.