• Title/Summary/Keyword: 경로 탐색 알고리즘

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Efficient State Space Generation for Guaranteeing a Natural-Looking Path for NPCs (NPC의 자연스러운 이동경로를 보장하는 효율적인 상태공간의 생성)

  • Yu, Kyeon-Ah
    • Journal of KIISE:Software and Applications
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    • v.34 no.4
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    • pp.368-376
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    • 2007
  • How to represent the search space is as important as which search algorithm to use for finding natural-looking paths for moving NPC (non-player character) in computer games. Recently, various state space representation methods which have been developed for computer games are being used while A* algorithm dominates as the preferred search algorithm. These representation methods show some drawbacks such as the size of state space is too large, there is no guarantee for optimality, the path found is not natural-looking, and the generation of nodes and links is not automatic by depending on a level designer. In this paper the requirements for natural-looking paths are introduced and to find paths satisfying these requirements, the use of the generalized visibility graphs which is the extended version of the visibility graph in Robotics is proposed.

S-MINE Algorithm for the TSP (TSP 경로탐색을 위한 S-MINE 알고리즘)

  • Hwang, Sook-Hi;Weon, Il-Yong;Ko, Sung-Bum;Lee, Chang-Hoon
    • The KIPS Transactions:PartB
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    • v.18B no.2
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    • pp.73-82
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    • 2011
  • There are a lot of people trying to solve the Traveling Salesman Problem (TSP) by using the Meta Heuristic Algorithms. TSP is an NP-Hard problem, and is used in testing search algorithms and optimization algorithms. Also TSP is one of the models of social problems. Many methods are proposed like Hybrid methods and Custom-built methods in Meta Heuristic. In this paper, we propose the S-MINE Algorithm to use the MINE Algorithm introduced in 2009 on the TSP.

Path-planning using Genetic Algorithm and Fuzzy Rule (유전자 알고리즘, 퍼지 룰을 이용한 다중 경로 계획)

  • Heo, Jeong-Min;Kim, Jung-Min;Jung, Sung-Young;Kim, Sung-Shin;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.60-63
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    • 2008
  • 본 논문에서는 신경망 모델(neural network model)과 유전자 알고리즘(genetic algorithm)을 이용한 실시간 경로 계획(real-time path-planning)과 퍼지 룰(fuzzy rule)을 이용한 효율적인 다중경로계획(multiple path-planning)을 제안한다. 실시간 경로 계획은 빠른 시간 내에 최적 경로의 생성이 반드시 수행되어야 하므로, 본 논문에서는 경로 계획 중 장애물 지역과 비장애물 지역을 빠르게 확인하기 위해 신경망 모델을 이용하여, 이동 방향 및 최적경로 탐색을 위하여 유전자 알고리즘을 이용하였다. 또한 충돌 구역에서의 효율적인 다중 경로 계획을 위해, 퍼지를 이용하여 경로를 재계획 하였다. 퍼지의 경우, 현재 위치에서 목표 지점으로의 방향을 계산하기 위한 퍼지 소속 함수와 현재 위치와 충돌 구역까지의 거리 값을 가중치로 세우고 퍼지 룰을 결정하여 경로계획을 수행하였다. 시뮬레이션을 통해 실험해본 결과, 퍼지 룰을 사용했을 때 사용하지 않았을 때 보다 좋은 성능을 나타남을 확인할 수 있었다.

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A Heuristic Path-Finding Scheme Based on the Road Hierarchy (도로망의 계층성을 이용한 휴리스틱 주행 경로 탐색)

  • 김기홍;유승원;강현민;차상균
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10a
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    • pp.183-185
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    • 1999
  • 주행 경로 안내는 최근 국내에서도 활발히 연구되고 있는 지능형 교통 시스템(ITS)의 주요 기능 중 하나이다. 주행 경로 안내를 위해서는 대규모 도로망에서 신속하게 경로를 찾는 방법과 찾은 경로를 음성 또는 기호로 운전자에게 효율적으로 안내하는 방법등이 필요하다. 본 논문에서는 도로망의 계층성을 휴리스틱 정보로 활용하여 최단시간 경로를 효율적으로 찾는 방법을 제안한다. 제안된 방법은 고속국도, 국도 등의 고속 주행용 도로만으로 소규모 상위 계층 도로망을 만들고 이를 기존 도로망에 덧붙이는 방식으로 통합한다. 이 통합망에 상위 계층 도로망을 우선적으로 찾도록 구성한 A* 알고리즘을 수행하여 최단시간 경로를 찾는다. 또 경로 탐색용 그래프가 디스크에 저장된 경우에, 디스크 접근을 최적화하기 위한 데이터베이스 설계 및 디스크 접근 방법을 기술한다. 제안된 방법의 효율성을 검증하기 위해 서울시 도로망 데이터를 이용하여 실험한 결과, 제안된 방법을 통해 경로 탐색 소요 시간, 디스크 입출력 회수, 메모리 사용량 등을 75%이상 줄일 수 있었다.

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Design and Implementation of the Postal Route Optimization System Model (우편 경로 최적화 시스템 모델 설계 및 구현)

  • Nam, Sang-U
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.6
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    • pp.1483-1492
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    • 1996
  • In this paper, related on the postal business with the GIS(Geographics Information System), it discusses design and implementation of the PROS(Postal Route Optimization System) model and its main module, the shortest path generation algorithm, for supporting to postal route managements. It explains examples requirements of postal route system, and suggests the efficient PROS model using our developed shortest path generation algorithm. Because the shortest path algorithm adopts not only consider the Dijkstra algorithm of graph theory, but also the method with the direction property, PROS can be implemented with fast and efficient route search. PROS is mainly constituted of the Shortest Generator, the Isochronal Area Generator, and the Path Rearrangement Generator. It also exploits the GIS engine and the spatial DBMS (Data Base Management System) for processing coordinates in the map and geographical features. PROS can be used in the management of postal delivery business and delivery area and route, and in the rearrangement of route. In the near future, it can be also applied to commercial delivery businesses, guides of routs and traffic informations, and auto navigation system with GPS(Global Positioning System).

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A Fuzzy Evaluation Method of Traveler's Path Choice in Transportation Network (퍼지평가방법을 이용한 교통노선 결정)

  • 이상훈;김덕영;김성환
    • Journal of Korean Society of Transportation
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    • v.20 no.1
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    • pp.65-76
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    • 2002
  • This study is realized using fuzzy evaluation and AHP(the analytic hierarchy process) for the optimum search of traffic route and estimated by the quantitative analysis in the vague subjective judgement. It is different from classical route search and noticed thinking method of human. Appraisal element, weight, appraisal value of route is extracted from basic of the opinion gathering fur the driving expert and example of route model was used for the finding of practice utility. Model assessment was performed attribute membership function making of estimate element, estimate value setting, weight define by the AHP, non additive presentation of weight according to $\lambda$-fuzzy measure, Choquet fuzzy integral.

An Economic Ship Routing System Based on a Minimal Dynamic-cost Path Search Algorithm (최소동적비용 경로탐색 알고리즘 기반 선박경제운항시스템)

  • Joo, Sang-Yeon;Cho, Tae-Jeong;Cha, Jae-Mun;Yang, Jin-Ho;Kwon, Yung-Keun
    • KIPS Transactions on Computer and Communication Systems
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    • v.1 no.2
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    • pp.79-86
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    • 2012
  • An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.

Implementation of Tactical Path-finding Integrated with Weight Learning (가중치 학습과 결합된 전술적 경로 찾기의 구현)

  • Yu, Kyeon-Ah
    • Journal of the Korea Society for Simulation
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    • v.19 no.2
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    • pp.91-98
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    • 2010
  • Conventional path-finding has focused on finding short collision-free paths. However, as computer games become more sophisticated, it is required to take tactical information like ambush points or lines of enemy sight into account. One way to make this information have an effect on path-finding is to represent a heuristic function of a search algorithm as a weighted sum of tactics. In this paper we consider the problem of learning heuristic to optimize path-finding based on given tactical information. What is meant by learning is to produce a good weight vector for a heuristic function. Training examples for learning are given by a game level-designer and will be compared with search results in every search level to update weights. This paper proposes a learning algorithm integrated with search for tactical path-finding. The perceptron-like method for updating weights is described and a simulation tool for implementing these is presented. A level-designer can mark desired paths according to characters' properties in the heuristic learning tool and then it uses them as training examples to learn weights and shows traces of paths changing along with weight learning.

Development of an Optimal Trajectory Planning Algorithm for Automated Pavement Crack Sealer (도로면 크랙실링 자동화 장비의 최적 경로계획 알고리즘 개발)

  • Yoo, Hyun-Seok;Lee, Jeong-Ho;Kim, Young-Suk
    • Korean Journal of Construction Engineering and Management
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    • v.11 no.4
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    • pp.68-79
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    • 2010
  • During the last two decades, several tele-operated and machine-vision-assisted systems have been developed in construction and maintenance area such as pavement crack sealing, sewer pipe rehabilitation, and excavation. In developing such tele-operated and machine-vision-assisted systems, trajectory plans are very important tasks for optimal motions of robots whether their environments are structured or unstructured. This paper presents an optimal trajectory planning algorithm used for a machine-vision-assisted automatic pavement crack sealing system. In this paper, the performance of the proposed optimal trajectory planning algorithm is compared with the greedy trajectory plans which are used in previously developed pavement crack sealing systems. The comparison is based on computational cost versus overall gains in crack sealing efficiency. Finally, it is concluded that the proposed algorithm plays an important role in productivity improvement of the automatic pavement crack sealing system developed.

Path Control Algorithm for AGV Using Right of Path Occupation (경로 점유권을 이용한 AGV의 경로 제어 알고리즘)

  • Joo, Young-Hoon;Kim, Jong-Seon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.5
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    • pp.592-598
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    • 2008
  • This paper presents collision prediction and avoidance method for AGVS (Automatic Guide Vehicle System). Also, we propose the PO(Right of Path Occupying) with decentralized delay time for collision avoidance. Classified essential element of AGV's working environment is modeled in this paper. Using this model, we propose a new shortest path algorithm using A* search algorithm and obtain the information on AGVs travel time, coordinates and rotation vector. Finally, we use the AGVs information data as input for simulation program. The simulation practice is used in order to evaluate a collision prediction and avoidance, and it has been presented to demonstrate the applicability of the minimize delay time.