• Title/Summary/Keyword: collision-free path planning

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유전 알고리즘을 이용한 이동로봇의 장애물 회피 (Collision Avolidance for Mobile Robot using Genetic Algorithm)

  • 곽한택;이기성
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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    • pp.279-282
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    • 1996
  • Collision avoidance is a method to direct a mobile robot without collision when traversing the environment. This kind of navigation is to reach a destination without getting lost. In this paper, we use a genetic algorithm for the path planning and collision avoidance. Genetic algorithm searches for path in the entire, continuous free space and unifies global path planning and local path planning. It is a efficient and effective method when compared with traditional collision avoidance algorithm.

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Efficient algorithm for planning collision free path among polyhedral obstacles

  • Habib, Maki-K.;Asama, Hajime
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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    • pp.1004-1008
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    • 1990
  • This research focuses on developing a new and computationally efficient algorithm for free space structuring and planning collision free paths for an autonomous mobile robot working in an environment populated with polygonal obstacles. The algorithm constructs the available free space between obstacles in terms of free convex area. A collision free path can be efficiently generated based on a graph constructed using the midpoints of common free links between free convex area as passing points. These points correspond to nodes in a graph and the connection between them within each convex area as arcs in this graph. The complexity of the search for collision free path is greatly reduced by minimizing the size of the graph to be searched concerning the number of nodes and the number of arcs connecting them. The analysis of the proposed algorithm shows its efficiency in terms of computation ability, safety and optimality.

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여유 자유도를 갖는 Robot Manipulator 최적 충돌 회피 경로 계획에 관한 연구 (Optimal Collision-Free Path Planning of Redundant Robotic Manipulators)

  • 장민근;기창두;기석호
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1996년도 추계학술대회 논문집
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    • pp.743-747
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    • 1996
  • A Potential Field Method is applied to the proposed algorithm for the planning of collision-free paths of redundant manipulators. The planning is carried out on the base of kinematic configuration. To make repulsive potentials, sources are distributed on the boundaries of obstacles. To escape from local minimum of the main potential and to attack other difficulties of the planning, various potentials are defined simultaneously, Inverse Kinematics Problems of the redundant manipulators are solved by unconstrained optimization method. Computer simulation result of the path planning is presented.

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다관절 로보트를 위한 충돌 회피 경로 계획 (Collision-Free Path Planning for Articulated Robots)

  • 최진섭;김동원
    • 대한산업공학회지
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    • 제22권4호
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    • pp.579-588
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    • 1996
  • The purpose of this paper is to develop a method of Collision-Free Path Planning (CFPP) for an articulated robot. First, the configuration of the robot is built by a set of robot joint angles derived from robot inverse kinematics. The joint space, that is made of the joint angle set, forms a Configuration space (Cspcce). Obstacles in the robot workcell are also transformed into the Cobstacles using slice projection method. Actually the Cobstacles means the configurations of the robot causing collision with obstacles. Secondly, a connected graph, a kind of roadmap, is constructed by the free configurations in the Cspace, where the free configurations are randomly sampled from a free Cspace immune from the collision. Thirdly, robot paths are optimally determinant in the connected graph. A path searching algorithm based on $A^*$ is employed in determining the paths. Finally, the whole procedures for the CFPP method are shown for a proper articulated robot as an illustrative example.

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신경회로망을 이용한 8축 로봇의 충돌회피 경로계획 (Collision-Avoidance Task Planning for 8 Axes-Robot Using Neural Network)

  • 최우형;신행봉;윤대식;문병갑;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 춘계학술대회 논문집
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    • pp.184-189
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    • 2002
  • Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. Path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

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신경회로망을 이용한 Dual-Arm 로봇의 충돌회피 최적작업계획 (Optimal Collision-Avoidance Task Planning for Dual-Arm Using Neural Network)

  • 최우형;신행봉;윤대식;문병갑;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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    • pp.244-249
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    • 2001
  • Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. Path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

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뉴럴 네트워크를 이용한 Dual-Arm 로봇의 충돌회피 최적작업계획 (Optimal Collision-Avoidance Task Planning for Dual-Arm Using Neural Network)

  • 최우형;정동연;배길호;김인수;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
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    • pp.113-118
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    • 2000
  • Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. Path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

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유전 알고리즘을 이용한 미지의 장애물이 존재하는 작업공간내 이동 로봇의 경로계획 (Path Planning for Mobile Robot in Unstructured Workspace Using Genetic Algorithms)

  • 조현철;이기성
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 G
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    • pp.2318-2320
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    • 1998
  • A genetic algorithm for global and local path planning and collision avoidance of mobil robot in unstructured workspace is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

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동적 변화의 작업환경 내에서 이동 로봇의 경로계획 (Path Planning for a Mobile Robot in Dynamic Working Environments)

  • 조현철;이기성
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 G
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    • pp.3098-3100
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    • 1999
  • A genetic algorithm for global and local path planning and collision avoidance of mobile robot in dynamic working environment is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

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Subgoal Generation Algorithm for Effective Composition of Path-Planning

  • Kim, Chan-Hoi;Park, Jong-Koo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1496-1499
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    • 2004
  • In this paper, we deal with a novel path planning algorithm to find collision-free path for a moving robot to find an appropriate path from initial position to goal position. The robot should make progress by avoiding obstacles located at unknown position. Such problem is called the path planning. We propose so called the subgoal generation algorithm to find an effective collision-free path. The generation and selection of the subgoal are the key point of this algorithm. Several subgoals, if necessary, are generated by analyzing the map information. The subgoal is the candidate for the final path to be pass through. Then selection algorithm is executed to choose appropriate subgoal to construct a correct path. Deep and through explanations are given for the proposed algorithm. Simulation example is given to show the effectiveness of the proposed algorithm.

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