• Title/Summary/Keyword: Obstacle problem

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A Method for k Nearest Neighbor Query of Line Segment in Obstructed Spaces

  • Zhang, Liping;Li, Song;Guo, Yingying;Hao, Xiaohong
    • Journal of Information Processing Systems
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    • v.16 no.2
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    • pp.406-420
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    • 2020
  • In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.

Path coordinator by the modified genetic algorithm

  • Chung, C.H.;Lee, K.S.
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1939-1943
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    • 1991
  • 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 shortest 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 of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. 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 Neural 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 proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

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OBSTACLE SHAPE RECONSTRUCTION BY LOCALLY SUPPORTED BASIS FUNCTIONS

  • Lee, Ju-Hyun;Kang, Sungkwon
    • Honam Mathematical Journal
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    • v.36 no.4
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    • pp.831-852
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    • 2014
  • The obstacle shape reconstruction problem has been known to be difficult to solve since it is highly nonlinear and severely ill-posed. The use of local or locally supported basis functions for the problem has been addressed for many years. However, to the authors' knowledge, any research report on the proper usage of local or locally supported basis functions for the shape reconstruction has not been appeared in the literature due to many difficulties. The aim of this paper is to introduce the general concepts and methodologies for the proper choice and their implementation of locally supported basis functions through the two-dimensional Helmholtz equation. The implementations are based on the complex nonlinear parameter estimation (CNPE) formula and its robust algorithm developed recently by the authors. The basic concepts and ideas are simple. The derivation of the necessary properties needed for the shape reconstructions are elementary. However, the capturing abilities for the local geometry of the obstacle are superior to those by conventional methods, the trial and errors, due to the proper implementation and the CNPE algorithm. Several numerical experiments are performed to show the power of the proposed method. The fundamental ideas and methodologies described in this paper can be applied to many other shape reconstruction problems.

A Study on the Obstacle Avoidance of a Robot Manipulator by Using the Neural Optimization Network (신경최적화 회로를 이용한 로봇의 장애물 회피에 관한 연구)

  • 조용재;정낙영;한창수
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.2
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    • pp.267-276
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    • 1993
  • This paper discusses the neural network application in the study on the obstacle avoidance of robot manipulator during the trajectory planning. The collision problem of two robot manipulators which are simultaneously moving in the same workspace is investigated. Instead of the traditional modeling method, this paper processing based on the calculation of joint angle in the cartesian coordinate with constrained condition shows the possibility of real time control. The problem of the falling into the local minima is cleared by the adaptive weight factor control using the temperature adding method. Computer simulations are shown for the verification.

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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Motion planning of a robot manipulator for time-varying obstacle avoidance using adaptive view-time (적응관측시간을 이용한 로보트 매니퓰레이터의 시변 장애물 회피 동작 계획)

  • 고낙용;최한수;이범희;고명삼
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.428-433
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    • 1993
  • An analytic solution approach to the time-varying obstacle avoidance problem is pursued. We use the view-time concept, especially the adaptive view-time. First. we introduce the adaptive view-time and analyze its properties. Next, we propose a view-time based motion planning method. The proposed method is applied and simulated for the collision-free motion planning of a 2 DOF robot manipulator. We simulate the robot motion under several different view-time systems. Generally, the motion planning with the adaptive view-time systems has some advantages over that with the fixed view-time systems.

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Proportional Navigation-Based Optimal Collision Avoidance for UAVs (비례항법을 이용한 무인 항공기의 최적 충돌 회피 기동)

  • 한수철;방효충
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.11
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    • pp.1065-1070
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    • 2004
  • Optimal collision avoidance algorithm for unmanned aerial vehicles based on proportional navigation guidance law is investigated this paper. Although proportional navigation guidance law is widely used in missile guidance problems, it can be used in collision avoidance problem by guiding the relative velocity vector to collision avoidance vector. The optimal navigation coefficient can be obtained if an obstacle if an obstacle moves at constant velocity vector. The stability of the proposed algorithm is also investigated. The stability can be obtained by choosing a proper navigation coefficient.

Intelligent Motion and Autonomous Maneuvering of Mobile Robots using Hybrid System (하이브리드 시스템을 이용한 이동로봇의 지능적 동작과 자율주행)

  • 이용미;임준홍
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.152-152
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    • 2000
  • In this paper, we propose a new approach to intelligent motion and autonomous maneuvering of mobile robots using hybrid system. In high Level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot as a low vevel are specified in the abstracted motions, The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments.

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Advanced electricity electron information communication facility obstacle factor and countermeasure investigation in digital age (디지털시대의 첨단 전기 전자 정보 통신설비 장애요인과 대책 고찰)

  • Kang, Tae-Keun
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2004.05a
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    • pp.110-115
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    • 2004
  • Examine merits and demerits and obstacle factor that exist to all direction of digital infratechnology that is supplied on industry whole according to development special quality of computer by development of computer and Information Technology and electricity electron information communication facility that basic impulse insulation level does not exist examined scorched earth or an interference problem factor and countermeasure of semiconductor degauss of factor and electricity electron information transmission system that is numbed or causes system down.

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Collaborative Obstacle Avoidance Method of Surface and Aerial Drones based on Acoustic Information and Optical Image (음향정보 및 광학영상 기반의 수상 및 공중 드론의 협력적 장애물회피 기법)

  • Man, Dong-Woo;Ki, Hyeon-Seung;Kim, Hyun-Sik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.7
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    • pp.1081-1087
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    • 2015
  • Recently, the researches of aerial drones are actively executed in various areas, the researches of surface drones and underwater drones are also executed in marine areas. In case of surface drones, they essentially utilize acoustic information by the sonar and consequently have the local information in the obstacle avoidance as the sonar has the limitations due to the beam width and detection range. In order to overcome this, more global method that utilizes optical images by the camera is required. Related to this, the aerial drone with the camera is desirable as the obstacle detection of the surface drone with the camera is impossible in case of the existence of clutters. However, the dynamic-floating aerial drone is not desirable for the long-term operation as its power consumption is high. To solve this problem, a collaborative obstacle avoidance method based on the acoustic information by the sonar of the surface drone and the optical image by the camera of the static-floating aerial drone is proposed. To verify the performance of the proposed method, the collaborative obstacle avoidances of a MSD(Micro Surface Drone) with an OAS(Obstacle Avoidance Sonar) and a BMAD(Balloon-based Micro Aerial Drone) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.