• Title/Summary/Keyword: path search algorithm

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An Analysis on Shortest Path Search Process of Gifted Student and Normal Student in Information (정보영재학생과 일반학생의 최단경로 탐색 과정 분석)

  • Kang, Sungwoong;Kim, Kapsu
    • Journal of The Korean Association of Information Education
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    • v.20 no.3
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    • pp.243-254
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    • 2016
  • This study has produced a checker of the shortest path search problem with a total of 19 questions as a web-based computer evaluation based on the 'TRAFFIC' questions of PISA 2012. It is because the computer has been settled as an indispensable and significant instrument in the process of solving the problems of everyday life and as a media that is underlying in assessment. Therefore, information gifted students should be able to solve the problem using the computer and give clear enough commands to the computer so that it can perform the procedure. In addition, since it is the age that the computational thinking is affecting every sectors, it should give students new educational stimuli. The relationship between the rate of correct answers and the time took to solve the problem through the shortest route search process showed a significant correlation the variable that affected the problem solving as the difficulty of the question rises due to the increase of nodes and edges turned out to be the node than the edge. It was revealed that information gifted students went through algorithmic thinking in the process of solving the shortest route search problem. And It could be confirmed cognitive characteristics of the information gifted students such as 'ability streamlining' and 'information structure memory'.

Elderly Assistance System Development based on Real-time Embedded Linux (실시간 임베디드 리눅스 기반 노약자 지원 로봇 개발)

  • Koh, Jae-Hwan;Yang, Gil-Jin;Choi, Byoung-Wook
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.11
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    • pp.1036-1042
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    • 2013
  • In this paper, an elderly assistance system is developed based on Xenomai, a real-time development framework cooperating with the Linux kernel. A Kinect sensor is used to recognize the behavior of the elderly and A-star search algorithm is implemented to find the shortest path to the person. The mobile robot also generates a trajectory using a digital convolution operator which is based on a Bezier curve for smooth driving. In order to follow the generated trajectory within the control period, we developed real-time tasks and compared the performance of the tracking trajectory with that of non real-time tasks. The real-time task has a better result on following the trajectory within the physical constraints which means that it is more appropriate to apply to an elderly assistant system.

Viewing Path Search and Congestion Control Algorithms For Comfortable Museum Viewing (편안한 박물관 관람을 위한 관람 경로 탐색 및 혼잡제어 알고리즘)

  • Seo, Yoon-Deuk;Ahn, Jin-Ho
    • Journal of Internet Computing and Services
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    • v.11 no.3
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    • pp.131-137
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    • 2010
  • Today, many museums are changing their forms with ubiquitous environment. Unlike traditional museums providing only static text-based information attached to its corresponding artifacts to visitors, those ubiquitous museums provide not only artifacts' text information, but also many different forms of information such as sound or media through personal digital assistance or cell phones. However, these existing ubiquitous museums still provide each visitor only with artifact-centric information in very simple ways. Also this disadvantageous feature causes high gallery congestion problem resulting from providing a uniform path for every visitor. These limitations may be the biggest barrier to providing more various and useful information about artifacts to visitors through considering each visitor's preference. This paper propose a new optimal viewing path search algorithm to provide comfortable museum viewing for each visitor according to its preference. Also, a new congestion control method is developed to protect visitors from being put in some hot spots on their museum viewing, improving its comfort to a maximum.

A Study on the Path Search for the Rapid Suppression of Naval Ships Casualties (함정 재해의 신속 진압을 위한 경로 탐색에 관한 연구)

  • Park, Ju-hun;Ruy, Won-Sun;Chung, Jung-Hoon;Kim, Sook-Kyoung
    • Journal of the Society of Naval Architects of Korea
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    • v.57 no.4
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    • pp.221-229
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    • 2020
  • Naval ships could be seriously damaged by enemy attacks in battle. Moreover, this damage could be spread and deteriorated into a secondary accident. Secondary accidents that have adverse effects on naval ship's survivability, such as fire, flood, smoke extension, and patient occurrence, are defined as casualties. These casualties sharply degrade the survivability of naval ships. Furthermore, naval ships could be burned-out and sunk by casualties in isolated sea. Therefore, damage control and rapid suppression of the casualties in the naval ships is essential. This study was conducted in the establishment of suppression paths according to the characteristics of each casualty so that the developed system can support the rapid suppression in an emergency and even the training situation on a regular state. To establish the suppression paths, the two-dimensional numerical map is designed by converting the three-dimensional features of the naval ships, and the well known algorithms are compared to present the appropriate one for path finding problem on the naval ships. Finally, we devised a specific routing algorithm that fits the characteristics of each casualty in accordance with the Korean Navy's doctrines and handbooks of casualty suppression.

Autonomous exploration for radioactive sources localization based on radiation field reconstruction

  • Xulin Hu;Junling Wang;Jianwen Huo;Ying Zhou;Yunlei Guo;Li Hu
    • Nuclear Engineering and Technology
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    • v.56 no.4
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    • pp.1153-1164
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    • 2024
  • In recent years, unmanned ground vehicles (UGVs) have been used to search for lost or stolen radioactive sources to avoid radiation exposure for operators. To achieve autonomous localization of radioactive sources, the UGVs must have the ability to automatically determine the next radiation measurement location instead of following a predefined path. Also, the radiation field of radioactive sources has to be reconstructed or inverted utilizing discrete measurements to obtain the radiation intensity distribution in the area of interest. In this study, we propose an effective source localization framework and method, in which UGVs are able to autonomously explore in the radiation area to determine the location of radioactive sources through an iterative process: path planning, radiation field reconstruction and estimation of source location. In the search process, the next radiation measurement point of the UGVs is fully predicted by the design path planning algorithm. After obtaining the measurement points and their radiation measurements, the radiation field of radioactive sources is reconstructed by the Gaussian process regression (GPR) model based on machine learning method. Based on the reconstructed radiation field, the locations of radioactive sources can be determined by the peak analysis method. The proposed method is verified through extensive simulation experiments, and the real source localization experiment on a Cs-137 point source shows that the proposed method can accurately locate the radioactive source with an error of approximately 0.30 m. The experimental results reveal the important practicality of our proposed method for source autonomous localization tasks.

Optimal solution search method by using modified local updating rule in ACS-subpath algorithm (부경로를 이용한 ACS 탐색에서 수정된 지역갱신규칙을 이용한 최적해 탐색 기법)

  • Hong, SeokMi;Lee, Seung-Gwan
    • Journal of Digital Convergence
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    • v.11 no.11
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    • pp.443-448
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    • 2013
  • Ant Colony System(ACS) is a meta heuristic approach based on biology in order to solve combinatorial optimization problem. It is based on the tracing action of real ants which accumulate pheromone on the passed path and uses as communication medium. In order to search the optimal path, ACS requires to explore various edges. In existing ACS, the local updating rule assigns the same pheromone to visited edge. In this paper, our local updating rule gives the pheromone according to the total frequency of visits of the currently selected node in the previous iteration. I used the ACS algoritm using subpath for search. Our approach can have less local optima than existing ACS and find better solution by taking advantage of more informations during searching.

A Flexible Branch and Bound Method for the Job Shop Scheduling Problem

  • Morikawa, Katsumi;Takahashi, Katsuhiko
    • Industrial Engineering and Management Systems
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    • v.8 no.4
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    • pp.239-246
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    • 2009
  • This paper deals with the makespan minimization problem of job shops. The problem is known as one of hard problems to optimize, and therefore, many heuristic methods have been proposed by many researchers. The aim of this study is also to propose a heuristic scheduling method for the problem. However, the difference between the proposed method and many other heuristics is that the proposed method is based on depth-first branch and bound, and thus it is possible to find an optimal solution at least in principle. To accelerate the search, when a node is judged hopeless in the search tree, the proposed flexible branch and bound method can indicate a higher backtracking node. The unexplored nodes are stored and may be explored later to realize the strict optimization. Two methods are proposed to generate the backtracking point based on the critical path of the current best feasible schedule, and the minimum lower bound for the makespan in the unexplored sub-problems. Schedules are generated based on Giffler and Thompson's active schedule generation algorithm. Acceleration of the search by the flexible branch and bound is confirmed by numerical experiment.

A Study about Additional Reinforcement in Local Updating and Global Updating for Efficient Path Search in Ant Colony System (Ant Colony System에서 효율적 경로 탐색을 위한 지역갱신과 전역갱신에서의 추가 강화에 관한 연구)

  • Lee, Seung-Gwan;Chung, Tae-Choong
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.237-242
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    • 2003
  • Ant Colony System (ACS) Algorithm is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP). In this paper, we introduce ACS of new method that adds reinforcement value for each edge that visit to Local/Global updating rule. and the performance results under various conditions are conducted, and the comparision between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with tile original ACS in terms of solution quality and computation speed to these problem.

Autonomous-flight Drone Algorithm use Computer vision and GPS (컴퓨터 비전과 GPS를 이용한 드론 자율 비행 알고리즘)

  • Kim, Junghwan;Kim, Shik
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.3
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    • pp.193-200
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    • 2016
  • This paper introduces an algorithm to middle-low price drone's autonomous navigation flight system using computer vision and GPS. Existing drone operative system mainly contains using methods such as, by inputting course of the path to the installed software of the particular drone in advance of the flight or following the signal that is transmitted from the controller. However, this paper introduces new algorithm that allows autonomous navigation flight system to locate specific place, specific shape of the place and specific space in an area that the user wishes to discover. Technology developed for military industry purpose was implemented on a lower-quality hobby drones without changing its hardware, and used this paper's algorithm to maximize the performance. Camera mounted on middle-low price drone will process the image which meets user's needs will look through and search for specific area of interest when the user inputs certain image of places it wishes to find. By using this algorithm, middle-low price drone's autonomous navigation flight system expect to be apply to a variety of industries.

Efficient Processing of All-farthest-neighbors Queries in Spatial Network Databases

  • Cho, Hyung-Ju
    • Journal of Korea Multimedia Society
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    • v.22 no.12
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    • pp.1466-1480
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    • 2019
  • This paper addresses the efficient processing of all-farthest-neighbors (AFN) queries in spatial network databases. Given a set of data points P={p1,p2,…,p|p|} in a spatial network, where the distance between two data points p and s, denoted by dist (p,s), is the length of the shortest path between them, an AFN query is defined as follows: find the farthest neighbor ω(p)∈P of each data point p such that dist(p,ω(p)) ≥ dist(p,s) for all s∈P. In this paper, we propose a shared execution algorithm called FAST (for All-Farthest-neighbors Search in spatial neTworks). Extensive experiments on real-world roadmaps confirm the efficiency and scalability of the FAST algorithm, while demonstrating a speedup of up to two orders of magnitude over a conventional solution.