• Title/Summary/Keyword: optimal path generation

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Finding Optimal Small Networks by Mathematical Programming Models (수리계획 모형을 이용한 최적의 작은 네트워크 찾기)

  • Choi, Byung-Joo;Lee, Hee-Sang
    • IE interfaces
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    • v.21 no.1
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    • pp.1-7
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    • 2008
  • In this paper we study the Minimum Edge Addition Problem(MEAP) to decrease the diameter of a graph. MEAP can be used for improving the serviceability of telecommunication networks with a minimum investment. MEAP is an NP-hard optimization problem. We present two mathematical programming models : One is a multi-commodity flow formulation and the other is a path partition formulation. We propose a branch-and-price algorithm to solve the path partition formulation to the optimality. We develop a polynomial time column generation sub-routine conserving the mathematical structure of a sub problem for the path partition formulation. Computational experiments show that the path partition formulation is better than the multi-commodity flow formulation. The branch-and-price algorithm can find the optimal solutions for the immediate size graphs within reasonable time.

A Performance Bound of Mu1ti-hop Mu1ti-Relay Wireless Communication Systems with Optimal Path Selection (다중-홉 다중-릴레이 무선 통신 시스템에서 최적 경로 선택 기법의 성능 한계)

  • Almuradov, Kamol;Park, Jin-Bae;Kim, Yun-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.1C
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    • pp.1-7
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    • 2011
  • Recently, multi-hop relay transmission has drawn much attention owing to its advantage of coverage extension at low power consumption. In this paper, we derive a performance bound of multi-hop communication systems with multiple amplify-and-forward relays when the optimal path is selected. The bound is derived in generalized Nakagami fading channels with different parameters for each hop by applying the geometric mean bound to the path signal-to-noise ratio (SNR) and obtaining the moment generation function of the bound. It is shown that the bound based on the geometric mean is closer to the actual performance of optimal path selection when the fading effect is small.

Local Path Generation Method for Unmanned Autonomous Vehicles Using Reinforcement Learning (강화학습을 이용한 무인 자율주행 차량의 지역경로 생성 기법)

  • Kim, Moon Jong;Choi, Ki Chang;Oh, Byong Hwa;Yang, Ji Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.9
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    • pp.369-374
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    • 2014
  • Path generation methods are required for safe and efficient driving in unmanned autonomous vehicles. There are two kinds of paths: global and local. A global path consists of all the way points including the source and the destination. A local path is the trajectory that a vehicle needs to follow from a way point to the next in the global path. In this paper, we propose a novel method for local path generation through machine learning, with an effective curve function used for initializing the trajectory. First, reinforcement learning is applied to a set of candidate paths to produce the best trajectory with maximal reward. Then the optimal steering angle with respect to the trajectory is determined by training an artificial neural network. Our method outperformed existing approaches and successfully found quality paths in various experimental settings, including the cases with obstacles.

Path Planning Using an Information Grid Map for Safe Navigation (안전한 주행을 위한 정보 격자지도 기반의 경로계획)

  • Jung, Min-Kuk;Park, Joong-Tae;Song, Jae-Bok
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.6
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    • pp.623-628
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    • 2012
  • Conventional path planning methods have focused on the generation of an optimal shortest path to the goal. However, this optimal path cannot guarantee safe navigation, because it can often lead to a narrow area. Therefore, we propose a Coulomb's law-based safe path planning method that uses an information grid map. The information grid map includes four types of information: occupied, empty, guide, and dangerous areas. A safe path can be generated away from the dangerous area and close to the guide area by repulsive and attractive forces, respectively. Experiments and simulations show that the proposed method can generate paths inside the safe region and is useful for safe navigation.

Generation of Cutting Layers and Tool Selection for 3D Pocket Machining (3차원 포켓가공을 위한 절삭층 형성 및 공구선정)

  • 경영민;조규갑
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.9
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    • pp.101-110
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    • 1998
  • In process planning for 3D pocket machining, the critical issues for the optimal process planning are the generation of cutting layers and the tool selection for each cutting layers as well as the other factors such as the determination of machining types, tool path, etc. This paper describes the optimal tool selection on a single cutting layer for 2D pocket machining, the generation of cutting layers for 3D pocket machining, the determination of the thickness of each cutting layers, the determination of the tool combinations for each cutting layers and also the development of an algorithm for determining the machining sequence which reduces the number of tool exchanges, which are based on the backward approach. The branch and bound method is applied to select the optimal tools for each cutting layer, and an algorithmic procedure is developed to determine the machining sequence consisting of the pairs of the cutting layers and cutting tools to be used in the same operation.

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An optimal and genetic route search algorithm for intelligent route guidance system (지능형 주행 안내 시스템을 위한 유전 알고리즘에 근거한 최적 경로 탐색 알고리즘)

  • Choe, Gyoo-Seok;Woo, Kwang-Bang
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.2
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    • pp.156-161
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    • 1997
  • In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

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Machine Diagnosis and Maintenance Policy Generation Using Adaptive Decision Tree and Shortest Path Problem (적응형 의사결정 트리와 최단 경로법을 이용한 기계 진단 및 보전 정책 수립)

  • 백준걸
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.2
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    • pp.33-49
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    • 2002
  • CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

Cooperative Path Planning of Dynamical Multi-Agent Systems Using Differential Flatness Approach

  • Lian, Feng-Li
    • International Journal of Control, Automation, and Systems
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    • v.6 no.3
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    • pp.401-412
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    • 2008
  • This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.

3-Dimensional Path Planning and Guidance using the Dubins Curve for an 3-DOF Point-mass Aircraft Model (Dubins 곡선을 이용한 항공기 3자유도 질점 모델의 3차원 경로계획 및 유도)

  • O, Su-Hun;Ha, Chul-Su;Kang, Seung-Eun;Mok, Ji-hyun;Ko, Sangho;Lee, Yong-Won
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.24 no.1
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    • pp.1-9
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    • 2016
  • In this paper, we integrate three degree of freedom(3DOF) point-mass model for aircraft and three-dimensional path generation algorithms using dubins curve and nonlinear path tracking law. Through this integration, we apply the path generation algorithm to the path planning, and verify tracking performance and feasibility of using the aircraft 3DOF point-mass model for air traffic management. The accuracy of modeling 6DOF aircraft is more accurate than that of 3DOF model, but the complexity of the calculation would be raised, in turn the rate of computation is more likely to be slow due to the increase of degree of freedom. These obstacles make the 6DOF model difficult to be applied to simulation requiring real-time path planning. Therefore, the 3DOF point-mass model is also sufficient for simulation, and real-time path planning is possible because complexity can be reduced, compared to those of the 6DOF. Dubins curve used for generating the optimal path has advantage of being directly available to apply path planning. However, we use the algorithm which extends 2D path to 3D path since dubins curve handles the two dimensional path problems. Control law for the path tracking uses the nonlinear path tracking laws. Then we present these concomitant simulation results.

Robotic rim deburring technique in car wheel (로보트 이용 자동차 휠의 림 디버링)

  • 박종오;전종업;조의경
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.1144-1148
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    • 1991
  • The problems occurred when developing a automatic wheel deburring system are to make effective flexibility in model change and the irregularity of the position/shape of the burr, to select optimal robotic manufacturing process and to develope optimal end effector. The locations where burr exists are on flange, rim and spoke. Here will be discussed the optimal solution for the removal of rim burr by using robot. The research can be summarized as the automatic robot path generation by recognizing rim contour and automatic deburring process technique. Various rim contour data is generated automatically when the sensor which is fixed to robot is moving with the parallel motion to the wheel center axis and this generated data is transferred to the data storage system and converted to the robot path data. The robotic tool system which is suitable to the rim deburring process is developed by integrating tool, compliance function and sensor. And factory automation system controlled by robot controller and PC is developed. This system shows good productivity and flexibility.

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