• Title/Summary/Keyword: collision free strategy

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Optimal Task Planning for Collision-Avoidance of Dual-Arm Robot Using Neural Network (신경회로망을 이용한 이중암 로봇의 충돌회피를 위한 최적작업계획)

  • 최우형
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2000.04a
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    • pp.176-181
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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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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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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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Implementation of Collision Free Strategy for Multi-Mobile Robot (다중로봇의 충돌회피전략 구현)

  • Kim, Dong-W.;Kim, Joo-Hyung;Kwak, Whan-Joo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2010.07a
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    • pp.51-54
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    • 2010
  • 본 논문에서는 포텐셜 필드 방법과 퍼지로직 시스템을 이용하여 멀티 모바일 로봇의 충돌회피를 위한 경로계획을 연구한다. 잘 알려진 포텐셜 필드 방법은 멀티 모바일 로봇 시스템에 있어서 각각의 로봇에 대한 전역경로를 계획하기 위해 사용되었으며, 퍼지로직 시스템은 각 로봇에 근접하는 혹은 진행하는 로봇의 경로를 가로막는 장애물과의 충돌을 피하고 안전하게 목적지에 도달하기 위한 지역경로를 계획하기 위해 이용되었다.

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

  • 최우형;신행봉;윤대식;문병갑;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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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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Optimal Collision-Avoidance Task Planning for Dual-Arm Using Neural Network (신경회로망을 이용한 Dual-Arm 로봇의 충돌회피 최적작업계획)

  • 최우형;신행봉;윤대식;문병갑;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2001.04a
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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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Optimal Collision-Avoidance Task Planning for Dual-Arm Using Neural Network (뉴럴 네트워크를 이용한 Dual-Arm 로봇의 충돌회피 최적작업계획)

  • 최우형;정동연;배길호;김인수;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2000.10a
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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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Collision-free Path Planning Using Genetic Algorithm (유전자 알고리즘을 이용한 충돌회피 경로계획)

  • Lee, Dong-Hwan;Zhao, Ran;Lee, Hong-Kyu
    • Journal of Advanced Navigation Technology
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    • v.13 no.5
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    • pp.646-655
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    • 2009
  • This paper presents a new search strategy based on models of evolution in order to solve the problem of collision-free robotic path planning. We designed the robot path planning method with genetic algorithm which has become a well-known technique for optimization, intelligent search. Considering the path points as genes in a chromosome will provide a number of possible solutions on a given map. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. The effectiveness of the proposed genetic algorithm in the path planning was demonstrated by simulation. The proposed search strategy is able to use multiple and static obstacles.

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Fuzzy Logic Based Navigation for Multiple Mobile Robots in Indoor Environments

  • Zhao, Ran;Lee, Dong Hwan;Lee, Hong Kyu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.4
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    • pp.305-314
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    • 2015
  • The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.

An Efficient Code Assignment Algorithm in Wireless Mesh Networks (무선 메쉬 네트워크에서의 효율적인 코드할당 알고리즘에 대한 연구)

  • Yeo, Jae-Hyun
    • Journal of Information Technology Applications and Management
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    • v.15 no.1
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    • pp.261-270
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    • 2008
  • Wireless Mesh Networks (WMNs) have emerged as one of the new hot topics in wireless communications. WMNs have been suggested for use in situations in which some or all of the users are mobile or are located in inaccessible environments. Unconstrained transmission in a WMN may lead to the time overlap of two or more packet receptions, called collisions or interferences, resulting in damaged useless packets at the destination. There are two types of collisions; primary collision, due to the transmission of the stations which can hear each other, and hidden terminal collision, when stations outside the hearing range of each other transmit to the same receiving stations. For a WMN, direct collisions can be minimized by short propagation and carrier sense times. Thus, in this paper we only consider hidden terminal collision while neglecting direct collisions. To reduce or eliminate hidden terminal collision, code division multiple access (CDMA) protocols have been introduced. The collision-free property is guaranteed by the use of spread spectrum communication techniques and the proper assignment of orthogonal codes. Such codes share the fixed channel capacity allocated to the network in the design stage. Thus, it is very important to minimize the number of codes while achieving a proper transmission quality level in CDMA WMNs. In this paper, an efficient heuristic code assignment algorithm for eliminating hidden terminal collision in CDMA WMNs with general topology.

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