• 한국군사과학기술학회지
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• 제24권1호
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• pp.61-69
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• 2021

Recently, autonomous navigation technology is actively being developed due to the increasing demand of an unmanned surface vehicle(USV). Local planning is essential for the USV to safely reach its destination along paths. the dynamic window approach(DWA) algorithm is a well-known navigation scheme as a local path planning. However, the existing DWA algorithm does not consider path line tracking, and the fixed weight coefficient of the evaluation function, which is a core part, cannot provide flexible path planning for all situations. Therefore, in this paper, we propose a new DWA algorithm that can follow path lines in all situations. Fixed weight coefficients were trained using reinforcement learning(RL) which has been actively studied recently. We implemented the simulation and compared the existing DWA algorithm with the DWA algorithm proposed in this paper. As a result, we confirmed the effectiveness of the proposed algorithm.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1097-1107
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• 2001

In this paper, the wall following navigation algorithm of the mobile robot using a mono vision system is described. The key points of the mobile robot navigation system are effective acquisition of the environmental information and fast recognition of the robot position. Also, from this information, the mobile robot should be appropriately controlled to follow a desired path. For the recognition of the relative position and orientation of the robot to the wall, the features of the corridor structure are extracted using the mono vision system, then the relative position, the offset distance and steering angle of the robot from the wall, is derived for a simple corridor geometry. For the alleviation of the computation burden of the image processing, the Kalman filter is used to reduce search region in the image space for line detection. Next, the robot is controlled by this information to follow the desired path. The wall following control scheme by the PD control scheme is composed of two control parts, the approaching control and the orientation control, and each control is performed by steering and forward-driving motion of the robot. To verify the effectiveness of the proposed algorithm, the real time navigation experiments are performed. Through the result of the experiments, the effectiveness and flexibility of the suggested algorithm are verified in comparison with a pure encoder-guided mobile robot navigation system.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.107-110
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• 2008

In this study, we propose a system for setting a Destination on CNS(Car Navigation System) or PNS(Personal Navigation System). The present Navigation does set the destination by only static method like name search, address search and wire telegraph telephone number search. But, the kind of setting a static destination does not reflect the dynamic moving situation. So we suggest setting the destination of navigation using Identifier of moving terminal. And it includes privacy protection on personal position information

• 한국항행학회논문지
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• 제27권4호
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• pp.365-373
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• 2023

무인 항공기는 다양한 분야에서 널리 활용되고 있으며, 실시간 경로 재계획은 이들 기기의 안전성과 효율성을 향상하는 핵심 요소이다. 본 논문에서는 RRT*와 LOSPO를 기반으로 한 실시간 경로 재계획 기법을 제안한다. 제안된 기법은 먼저 RRT* 알고리즘을 활용하여 초기 경로를 생성하고, LOSPO를 이용하여 경로를 최적화한다. 또한 최적화된 경로를 궤적으로 변경하여 실제 시간과 항공기의 동적한계를 고려할 수 있다. 이 과정에서 환경 변화와 충돌 위험을 실시간으로 감지하고, 필요한 경우 경로를 재계획함으로써 안전한 운행을 유지한다. 이 방법은 시뮬레이션을 통한 실험을 통해 검증되었다. 본 논문의 결과는 무인 항공기의 실시간 경로 재계획에 관한 연구에 중요한 기여할 것으로 기대한다. 또한 이 기법을 다양한 상황에 적용함으로써 무인 항공기의 안전성과 효율성을 향상시킬 수 있다.

• 한국멀티미디어학회논문지
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• 제9권11호
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• pp.1483-1495
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• 2006

이동망(Navigation Mesh)은 캐릭터가 이동할 수 있는 다각형(삼각형) 집합으로 지형을 표현한다. 이동망은 자동화된 생성이 가능하며, 유연하게 3차원 공간을 표현할 수 있다. 지형 구조에 따라 삼각형 수를 달리함으로써 다양한 표현이 가능하며, 캐릭터는 3차원 상태 공간을 2차원 평면 공간으로 표현한 이동망으로만 이동하기 때문에 효율적인 이동과 경로 계획을 보장받을 수 있다. 그러나 현실적인 캐릭터의 이동을 위해 보다 많은 삼각형을 이용하여 지형을 표현함으로 경로 계획 수립 시 많은 상태 공간(다각형)을 검색하여 효율적인 탐색이 이루어지지 않는다. 본 논문에서는 이동망으로 표현된 3차원 게임에서에서의 효율적인 경로 탐색 방법을 위한 가시성 검사 시법을 제안한다. 정교한 다각형으로 이루어진 세밀한 지형에 그래프 기반 탐색을 적용하면 탐색할 공간이 많기 때문에 효율적인 탐색이 이루어지지 않는다. 그래서 본 논문에서는 정교하게 구성되어 있는 3차원 지형에서 효율적인 탐색이 이루어질 수 있도록 가시성 검사(visibility test)를 이용하여 탐색 공간을 줄이는 방법을 사용하였다. 장애물의 정점을 찾고 추정 함수(heuristic function)를 이동망을 지나가는 거리로 정의함으로서, 직선거리를 추정 함수로 정의한 그래프 기반 탐색 방법보다 탐색 영역을 현저하게 줄일 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1845-1865
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• 2019

Current Internet is designed by lots of service providers with different objects and policies which make the direct deployment of radically new architecture and protocols on Internet nearly impossible without reaching a consensus among almost all of them. Network virtualization is proposed to fend off this ossification of Internet architecture and add diversity to the future Internet. As an important part of network virtualization, virtual network embedding (VNE) problem has received more and more attention. In order to solve the problems of large embedding cost, low acceptance ratio (AR) and environmental adaptability in VNE algorithms, cognitive method is introduced to improve the adaptability to the changing environment and a cognitive virtual network embedding algorithm based on weighted relative entropy (WRE-CVNE) is proposed in this paper. At first, the weighted relative entropy (WRE) method is proposed to select the suitable substrate nodes and paths in VNE. In WRE method, the ranking indicators and their weighting coefficients are selected to calculate the node importance and path importance. It is the basic of the WRE-CVNE. In virtual node embedding stage, the WRE method and breadth first search (BFS) algorithm are both used, and the node proximity is introduced into substrate node ranking to achieve the joint topology awareness. Finally, in virtual link embedding stage, the CPU resource balance degree, bandwidth resource balance degree and path hop counts are taken into account. The path importance is calculated based on the WRE method and the suitable substrate path is selected to reduce the resource fragmentation. Simulation results show that the proposed algorithm can significantly improve AR and the long-term average revenue to cost ratio (LTAR/CR) by adjusting the weighting coefficients in VNE stage according to the network environment. We also analyze the impact of weighting coefficient on the performance of the WRE-CVNE. In addition, the adaptability of the WRE-CVNE is researched in three different scenarios and the effectiveness and efficiency of the WRE-CVNE are demonstrated.

• Journal of Electrical Engineering and Technology
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• 제10권2호
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• pp.676-687
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• 2015

Path planning algorithms are used to allow mobile robots to avoid obstacles and find ways from a start point to a target point. The general path planning algorithm focused on constructing of collision free path. However, a high continuous path can make smooth and efficiently movements. To improve the continuity of the path, the searched waypoints are connected by the proposed polynomial interpolation. The existing polynomial interpolation methods connect two points. In this paper, point groups are created with three points. The point groups have each polynomial. Polynomials are made by matching the differential values and simple matrix calculation. Membership functions are used to distribute the weight of each polynomial at overlapped sections. As a result, the path has $G^2$ continuity. In addition, the proposed method can analyze path numerically to obtain curvature and heading angle. Moreover, it does not require complex calculation and databases to save the created path.

• Journal of Positioning, Navigation, and Timing
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• 제2권2호
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• pp.123-130
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• 2013

Autonomous agricultural machines that are operated in small-scale farmland frequently experience turning and changes in direction. Thus, unlike when they are operated in large-scale farmland, the steering control systems need to be controlled precisely so that travel errors can be minimized. This study aims to develop a control algorithm for improving the path tracking performance of a steering system by analyzing the effect of the setting of the waypoint, which serves as the reference point for steering when an autonomous agricultural machine moves along a path or a coordinate, on control errors. A simulation was performed by modeling a 26-hp tractor steering system and by applying the equations of motion of a tractor, with the use of a computer. Path tracking errors could be reduced using an algorithm which sets the waypoint for steering on a travel path depending on the radius of curvature of the path and which then controls the speed and steering angle of the vehicle, rather than by changing the steering speed or steering ratio which are dependent on mechanical performance.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권1호
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• pp.33-40
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• 2000

In this paper, an integrated method for the path planning and motion control of wheeled mobile robots using a hybrid system model and control is presented. The hybrid model including the continuous dynamics and discrete dynamics with the continuous and discrete state vector is derived for a two wheel driven mobile robot. The architecture of the hybrid control system for real time path planning and following is designed which has the 3-layered hierarchical structure : the discrete event system using the digital automata as the higher process, the continuous state system for the wheel velocity controls as the lower process, and the interface system as the interaction process between the continuous system as the low level and the discrete event system as the high level. The reference motion commands for autonomous navigation are generated by the abstracted motion in the discrete event system. The motion control tasks including the feasible path planning and autonomous motion control with various initial conditions are investigated as the applications by the simulation studies.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.429-435
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• 2011

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.