• 로봇학회논문지
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• 제5권4호
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• pp.332-338
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• 2010

This paper presents a study of path-planning method for AGV(automated guided vehicle) based on path-tracking. It is important to find an optimized path among the AGV techniques. This is due to the fact that the AGV is conditioned to follow the predetermined path. Consequently, the path-planning method is implemented directly affects the whole AGV operation in terms of its performance efficiency. In many existing methods are used optimization algorithms to find optimized path. However, such methods are often prone with problems in handling the issue of inefficiency that exists in system's operation due to inherent undue time delay created by heavy load of complex computation. To solve such problems, we offer path-planning method using modified binary tree. For the purpose of our experiment, we initially designed a AGV that is equiped with laser navigation, two encoders, a gyro sensor that is meant to be operated within actual environment with given set of constrictions and layout for the AGV testing. The result of our study reflects the fact that within such environments, the proposed method showed improvement in its efficiency in finding optimized path.

• ETRI Journal
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• 제40권4호
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• pp.446-457
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• 2018

Robot navigation allows robot mobility. Therefore, mobility is an area of robotics that has been actively investigated since robots were first developed. In recent years, interest in personal service robots for homes and public facilities has increased. As a result, robot navigation within the home environment, which is an indoor environment, is being actively investigated. However, the problem with conventional navigation algorithms is that they require a large computation time for their building mapping and path planning processes. This problem makes it difficult to cope with an environment that changes in real-time. Therefore, we propose a humanoid robot navigation algorithm consisting of an image processing and optimization algorithm. This algorithm realizes navigation with less computation time than conventional navigation algorithms using map building and path planning processes, and can cope with an environment that changes in real-time.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권6호
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• pp.771-780
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• 2016

Detecting a set of longest paths is one of the crucial steps in static timing analysis and optimization. Recently, the process variation during manufacturing affects performance of the circuit design due to nanometer feature size. Measuring the performance of a circuit prior to its fabrication requires a considerable amount of computation time because it requires multi-corner and multi-mode analysis with process variations. An efficient algorithm of detecting the K-most critical paths in multi-corner multi-mode static timing analysis (MCMM STA) is proposed in this paper. The ISCAS'85 benchmark suite using a 32 nm technology is applied to verify the proposed method. The proposed K-most critical paths detection method reduces about 25% of computation time on average.

• 로봇학회논문지
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• 제18권3호
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• pp.337-345
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• 2023

In this paper, we propose a 3D LiDAR sensor-based costmap generation and path planning algorithm using it for reliable autonomous flight in complex indoor environments. 3D path planning is essential for reliable operation of UAVs. However, existing grid search-based or random sampling-based path planning algorithms in 3D space require a large amount of computation, and UAVs with weight constraints require reliable path planning results in real time. To solve this problem, we propose a method that divides a 3D space into several 2D spaces and a path planning algorithm that considers the distance to obstacles within each space. Among the paths generated in each space, the final path (Best path) that the UAV will follow is determined through the proposed objective function, and for this purpose, we consider the rotation angle of the 2D space, the path length, and the previous best path information. The proposed methods have been verified through autonomous flight of UAVs in real environments, and shows reliable obstacle avoidance performance in various complex environments.

• 한국군사과학기술학회지
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• 제13권5호
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• pp.824-830
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• 2010

It is not easy job to find a underwater target using sonar system in the ASW operations. Many researchers have tried to solve anti-submarine search problem aiming to maximize the probability of detection under limited searching conditions. The classical 'Search Theory' deals with search allocation problem and search path problem. In both problems, the main issue is to prioritize the searching cells in a searching area. The number of possible searching path that is combination of the consecutive searching cells increases rapidly by exponential function in the case that the number of searching cells or searchers increases. The more searching path we consider, the longer time we calculate. In this study, an effective algorithm that can maximize the probability of detection in shorter computation time is presented. We show the presented algorithm is quicker method than previous algorithms to solve search problem through the comparison of the CPU computation time.

• 한국통신학회논문지
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• 제29권12C호
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• pp.1722-1728
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• 2004

다수의 인증 경로가 존재하는 PKI 구조에서 인증 경로를 설정하는 것은 중요한 문제이다. 경로 설정은 다양한 검증을 통해 이루어지고 검증이 많을수록 경로의 유효성은 높아진다. 유효성 높은 경로의 선택은 경로 설정 및 검증 작업의 반복 횟수를 감소시킴으로서 고속의 인증서 검증이 가능하도록 하는 반면에 하나의 경로를 설정하는데 소요되는 시간 및 부담을 증가시킨다는 문제점을 가진다. 본 논문에서는 보다 적은 부합으로 경로의 유효성을 높일 수 있는 효율적인 인증 경로 설정 알고리즘을 제안한다.

• 품질경영학회지
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• 제11권2호
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• pp.10-17
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• 1983

The former paper (Part I) studies two methods for searching and determining the simple paths in an acyclic or a cyclic network. The two methods are computer programmed as subroutines (SPLP1 and SPLP2) for various use. And a few examples of its applications are discussed Another paper (Par II) studies the reliability computation for a network by using the Event Space Methods. A computer program is developed for the computation by applying the SPLP2 subroutine subprogram. In this paper the former results are summarized with another computer program for reliability computation by using the Path Tracing Methods. The two subroutines appear in the Appendix as reference for others. The programs can be used in the reliability computation of reducible and irreducible structure networks.

• 한국자동차공학회논문집
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• 제22권3호
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• pp.241-249
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• 2014

This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.256-256
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• 2000

In this parer, we present a real-time path planning algorithm which is integrated the artificial potential field(APF) and simulated annealing(SA) methods for mobile robot. The APF method in path planning has gained popularity since 1990's. It doesn't need the modeling of the complex configuration space of robot, and is easy to apply the path planning with simple computation. However, there is a major problem with APF method. It is the formation of local minima that can trap the robot before reaching its goal. So, to provide local minima recovery, we apply the SA method. The effectiveness of the proposed algorithm is verified through simulation.

• 제어로봇시스템학회논문지
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• 제16권1호
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• pp.53-60
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• 2010

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.