• 농촌계획
• /
• 제11권1호
• /
• pp.1-8
• /
• 2005

The purpose of this study is to develop a simulation model of rural road path for infrastructure of green-tourism and public service in rural areas. This study makes an objective function for moving cost minimization considering car travel time according to road characteristics, which can route the optimal shortest road paths between the center places and all rear villages, based on GIS coverages of road-village network for connecting between center places and rural villages as input data of the model. In order to verify the model algorithm, a homogeneous hexagonal network, assuming distribution of villages with same population density and equal distance between neighborhood villages on a level plane area, was tested to simulate the optimal paths between the selected center nodes and the other rear nodes, so that the test showed reasonable shortest paths and road intensity defined in this study. The model was also applied to the actual rural area, Ucheon-myun, which is located on Hoengsung-gun, Kangwon-do, with 72 rural villages, a center village (Uhang, 1st center place) in the area, a county conte. (Hoengsung-eup, 2nd center place), and a city (Wonju, 3rd center place), as upper settlement system. The three kinds of conte. place, Uhang, Hoengsung-eup, and Wonju, were considered as center places of three scenarios to simulate the optimal shortest paths between the centers and rural villages, respectively. The simulation results on the road-village network with road information about pavement and width of road show that several spans having high intensity of road are more important that the others, while some road spans have low intensity of road.

• 전자공학회논문지B
• /
• 제29B권11호
• /
• pp.36-45
• /
• 1992

A numerical trajectory planning method for path-constrained trajectory planning is proposed which ensures collision-free and time-optimal motions for two robotic manipulators with limited actuator torques and velocities. For each robot, physical constraints of the robots such as limited torques or limited rotational velocities of the actuators are converted to the constraints on velocity and acceleration along the path, which is described by a scalar variable denoting the traveled distance from starting point. Collision region is determined on the coordination space according to the kinematic structures and the geometry of the paths of the robots. An Extended Coordination Space is then constructed` an element of the space determines the postures and the velocities of the robots, and all the constraints described before are transformed to some constraints on the behaviour of the coordination-velocity curves in the space. A dynamic programming technique is them provided with on the discretized Extended Coordination Space to derive a collision-free and time-optimal trajectory pair. Numerical example is included.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• pp.1939-1943
• /
• 1991

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

• 한국전자통신학회논문지
• /
• 제18권5호
• /
• pp.981-988
• /
• 2023

무인 비행체의 활용범위가 확대됨에 따라 관련 기술의 발전과 기술 수요도 증가하는 추세이다. 무인 비행체의 운영빈도가 늘어나고 운영의 편리성이 강조됨에 따라 관련 자율비행 기술도 중요성이 주목받고 있다. 무인 비행체의 자율 비행에 있어 목적지에 도달하는 경로계획을 세우는 일은 유도제어에서 중요하며 무인화의 효과를 극대화하기 위해서는 경로계획 역시 자동으로 생성하는 기술이 필요하다. 본 논문에서는 무인 비행체의 자율운영 효과를 높이기 위해서 급속탐색랜덤트리기법으로 생성된 경로를 무인기의 특성에 맞게 최적화하는 기법에 관한 연구를 수행하였다. 최적 거리, 최단 시간, 임무점 통과 등의 지표를 달성하기 위해 경로계획을 무인 비행체의 임무 목표와 동적 특성을 고려하여 최적화하였다. 제안한 기법은 장애물 상황에 대한 성능검증을 통해 무인 비행체 경로계획 생성에 적용 가능성을 확인하였다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.601-606
• /
• 1998

In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• 한국군사과학기술학회지
• /
• 제15권3호
• /
• pp.272-287
• /
• 2012

The optimal use of sonar systems for detection is a practical problem in a given ocean environment. In order to quantify the mission achievability in general, measure of effectiveness(MOE) is defined for specific missions. In this paper, using the specific MOE for detection, which is represented as cumulative detection probability(CDP), an integrated software package named as Optimal Acoustic Search Path Planning(OASPP) is developed. For a given ocean environment and sonar systems, the discrete observations for detection probability(PD) are used to calculate CDP incorporating sonar and environmental parameters. Also, counter-detection probability is considered for vulnerability analysis for a given scenario. Through modeling and simulation for a simple case for which an intuitive solution is known, the developed code is verified.

• 한국정밀공학회지
• /
• 제14권7호
• /
• pp.49-58
• /
• 1997

In process planning for pocket machining, the selection of tool size, tool path, overlap distance, and the calculation of machining time are very important factors to obtain the optimal process planning result. Among those factors, the tool size is the most important one because the others depend on tool size. And also, it is not easy to determine the optimal tool size even though the shape of pocket is simple. Therefore, the optimal selection of tool size is the most essential task in process planning for machining a pocket. This paper presents a method for selecting optimal toos in pocket machining. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.

• 제어로봇시스템학회논문지
• /
• 제15권12호
• /
• pp.1232-1239
• /
• 2009

This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.

• 대한교통학회지
• /
• 제14권1호
• /
• pp.51-67
• /
• 1996

The optimal path-finding problem becomes complicated when multiple variables are simultaneously considered such as physical route length, degree of congestion, traffic capacity of intersections, number of intersections and lanes, and existence of free ways. Therefore, many researchers in various fields (management science, computer science, applied mathematics, production planning, satellite launching) attempted to solve the problem by ignoring many variables for problem simplification, by developing intelligent algorithms, or by developing high-speed hardware. In this research, an integration of expert system technique and case-based reasoning in high level with a conventional algorithms in lower level was attempted to develop an optimal path-finding system. Early application of experienced driver's knowledge and case data accumulated in case base drastically reduces number of possible combinations of optimal paths by generating promising alternatives and by eliminating non-profitable alternatives. Then, employment of a conventional optimization algorithm provides faster search mechanisms than other methods such as bidirectional algorithm and $A^*$ algorithm. The conclusion obtained from repeated laboratory experiments with real traffic data in Seoul metropolitan area shows that the integrated approach to finding optimal paths with consideration of various real world constraints provides reasonable solution in a faster way than others.

• Journal of Radiation Protection and Research
• /
• 제30권1호
• /
• pp.17-25
• /
• 2005

원자력 발전의 안정성이 사회적 문제로 제기된 이후 작업종사자에 대한 작업 중 방사선 피폭량에 대한 관심이 높아지고 있다. 현재의 방법에 의하면 방사선 작업 계획의 수립 시 작업 공간 내 선량률이 일정하다는 가정 하에 피폭선량을 예측하므로 작업 경로에 따른 피폭선량의 변화에 대한 고려가 이루어지지 않고 있다. 본 연구에서는 작업자와 선원과의 거리가 고려되 수정된 방사선 피폭량 계산식을 이용하여 방사성 폐기물 저장시설에서의 작업 중 작업경로 변화에 따른 방사선 피폭량을 계산하였다. 이 계산식을 이용하여 주어진 작업 공간과 선원 조건하에서 작업 중 방사선 피폭량을 최소로 하는 최적 작업경로를 탐색할 수 있는 수치해석 알고리즘을 제안하였다. 이를 위하여 2차원 작업공간에서 무한개의 작업경로를 유한개의 경로로 근사화하고 근사화된 모든 작업경로 중 피폭선량이 최소가 되는 작업경로를 탐색하였다. 또한, 3차원 그래픽 기술과 Java 프로그래밍을 이용한 가상작업 시뮬레이션 프로그램을 개발하고 작업 공간의 선량률 가시화 및 가상 작업 시뮬레이션을 수행하여 방사선 작업 계획의 수립을 위한 도구로서의 가능성을 검토하였다. 수치해석 계산과 시뮬레이션 과정을 통하여 최적 작업경로는 작업자와 선원과의 거리를 증가시키고 작업 시간을 단축시킬 수 있는 경로로 제시되었고, 이를 바탕으로 방사선 피폭량은 작업시간뿐만 아니라 작업자와 선원간의 거리에 영향을 받음과 최적화된 방사선 방호를 위해 작업경로가 고려되어야 함을 확인하였다.