• Title/Summary/Keyword: Shortest Path Algorithm

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Path planning method for mobile robot (이동 Robot를 위한 경로계획법)

  • 범희락;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.722-725
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    • 1990
  • This paper proposes a new path planning method for obstacle avoidance of mobile robot. In order to achieve easy planning of the path, a simple representation of the empty space is achieved based on thinning algorithm. The proposed Planning technique facilitates the direct use of information obtained by camera. Comparing to the V-graph method, the task of determining the shortest path from the resulting skeleton of empty space is optimized in terms of number of computation steps. The usefulness of the proposed method is ascertained by simulation.

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A Proactive Dissemination Protocol using Residual Energy and Signal Strength for WSNs (무선 센서 네트워크에서 에너지 잔량과 신호세기를 이용한 데이터 전송 프로토콜)

  • Park, Soo-Yeon;Kim, Moon-Seong;Jeong, Eui-Hoon;Bang, Young-Cheo
    • Journal of Internet Computing and Services
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    • v.11 no.4
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    • pp.33-39
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    • 2010
  • In this paper, a data dissemination protocol that transmits data collected for Wireless Sensor Networks (WSNs) is newly proposed, and the proposed proactive protocol takes into account energy consumption minimized and delay time disseminated. The well-known SPMS (Shortest Path Mined SPIN) forms the shortest path-based routing table obtained by Bellman Ford Algorithm (BFA) and disseminates data using a multi-hop path in order to minimize energy consumption. The mentioned properties of SPMS cause memory burden to create and maintain the routing tables. In addition, whenever BFA is executed, it is necessary to suffer from the energy consumption and traffic occurred. In order to overcome this problem, a proactive dissemination protocol using Residual Energy and Signal Strength, called RESS, is proposed in this paper. Simulation results show that RESS outperforms SPMS up to 84% in terms of the number of traffic messages and the transmitted delay time of RESS is similar to that of SPMS using the shortest path.

A Path & Velocity Profile Planning Based on A* Algorithm for Dynamic Environment (동적 환경을 위한 A* 알고리즘 기반의 경로 및 속도 프로파일 설계)

  • Kwon, Min-Hyeok;Kang, Yeon-Sik;Kim, Chang-Hwan;Park, Gwi-Tae
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.5
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    • pp.405-411
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    • 2011
  • This paper presents a hierarchical trajectory planning method which can handle a collision-free of the planned path in complex and dynamic environments. A PV (Path & Velocity profile) planning method minimizes a sharp change of orientation and waiting time to avoid a collision with moving obstacle through detour path. The path generation problem is solved by three steps. In the first step, a smooth global path is generated using $A^*$ algorithm. The second step sets up the velocity profile for the optimization problem considering the maximum velocity and acceleration. In the third step, the velocity profile for obtaining the shortest path is optimized using the fuzzy and genetic algorithm. To show the validity and effectiveness of the proposed method, realistic simulations are performed.

A Shortest Path Routing Algorithm using a Modified Hopfield Neural Network (수정된 홉필드 신경망을 이용한 최단 경로 라우팅 알고리즘)

  • Ahn, Chang-Wook;Ramakrishna, R.S.;Choi, In-Chan;Kang, Chung-Gu
    • Journal of KIISE:Information Networking
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    • v.29 no.4
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    • pp.386-396
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    • 2002
  • This paper presents a neural network-based near-optimal routing algorithm. It employs a modified Hopfield Neural Network (MHNN) as a means to solve the shortest path problem. It uses every piece of information that is available at the peripheral neurons in addition to the highly correlated information that is available at the local neuron. Consequently, every neuron converges speedily and optimally to a stable state. The convergence is faster than what is usually found in algorithms that employ conventional Hopfield neural networks. Computer simulations support the indicated claims. The results are relatively independent of network topology for almost all source-destination pairs, which nay be useful for implementing the routing algorithms appropriate to multi -hop packet radio networks with time-varying network topology.

Case Study for Telecommunication Network Design based on Optimal Path Algorithm (최적경로 알고리듬을 활용한 경제적인 통신망 설계 적용 사례)

  • Jung, Ju-Young;Choi, Yun-Soo;Jun, Chul-Min;Cho, Seong-Kil
    • Journal of Korea Spatial Information System Society
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    • v.8 no.1 s.16
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    • pp.107-118
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    • 2006
  • In this paper, several network algorithms were tested to find an optimal one for telecommunication network design. Algorithms such as Dijkstra's shortest path algorithm, Ford-Bellman's shortest path algorithm, Prim's minimum spanning tree algorithm, and Kruscal's minimum spanning tree algorithm were reviewed and compared in terms of feasibility and resulted network construction cost. Then an optimal algorithm that is most suitable for telecommunication network design was selected. For more specific and quantitative analysis of the selected algorithm, it was implemented to a real telecommunication network construction site. The analyzed results showed that the suggested design method when compared with the conventional one, reduced the network construction cost considerably. The total network length estimated by the conventional method were 5267 meters while the suggested method resulted in 4807 meters. Thus the new method reduced the total network length by 8.7 percent which is equivalent to 97,469,000 Won of construction cost. Considering the frequent telecommunication network constructions, due to new urban developments in the nation, the economic benefit of the suggested telecommunication network design method will be significant. In addition to the construction cost savings, the suggested telecommunication network design procedure possesses several other economic benefits. Since the design procedure can be standardized and automatized, it can reduce the design cost itself and the skill acquirement periods required for new or inapt design crews. Further, due to the standardized and automatized design procedure, any telecommunication network design results can accessed more objectively.

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Mobile Agent Based Route Search Method Using Genetic Algorithm (유전 알고리즘을 이용한 이동 에이전트 기반의 경로 탐색 기법)

  • Ji, Hong-il
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.9
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    • pp.2037-2043
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    • 2015
  • Proposed algorithm in this thesis introduced cells, units of router group, to conduct distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm. Also, through this experiment, in case of a network was damaged in existing optimal path algorithm, Dijkstra algorithm, the proposed algorithm was designed to route an alternative path and also as it has a 2nd shortest path in cells of the damaged network so it is faster than Dijkstra algorithm, The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

Recursive compensation algorithm application to the optimal edge selection

  • Chung, C.H.;Lee, K.S.
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.79-84
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    • 1992
  • 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 optimal 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, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). 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 Hopfield 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 used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

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