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首页> 外文期刊>Romanian journal of information science and technology >Maintaining a Minimum Spanning Tree for Kinetic Autonomous Robots in 2D-Euclidean Plane
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Maintaining a Minimum Spanning Tree for Kinetic Autonomous Robots in 2D-Euclidean Plane

机译:在2D欧式平面上为运动自主机器人维护最小生成树

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This paper presents a procedure for maintaining a 2D-Euclidean Minimum Spanning Tree for a set of n autonomous kinetic robots having no central supervision. The proposed procedure is based on the Kinetic data structure framework and the well known fact that the edges of the minimum spanning tree for a given set of points in the 2D-Euclidean domain are contained in the edges of its Delaunay triangulation. The kinetic data structure framework has a centralized data structure along with a priority queue on which a proposed algorithm works to maintain a combinatorial geometrical structure for a set of geometric objects. In this work, we propose an approach where the computation of the geometrical structure is done through the geometrical objects, in our case, the computations being done by the robots themselves. This is unlike that of maintaining a centralized data structure in the kinetic data structure framework. The kinetic autonomous robots, each being a computing object do all computations by themselves and update the spanning tree as the tree changes. In terms of kinetic data structure metrics, our data structure is local and compact.
机译:本文提出了一种程序,用于维护一组n个没有中央监督的自治动力学机器人的2D-欧式最小生成树。所提出的过程基于动力学数据结构框架,并且众所周知的事实是,二维欧氏域中给定点集的最小生成树的边缘包含在其Delaunay三角剖分的边缘中。动力学数据结构框架具有集中式数据结构以及优先级队列,在该优先级队列上,所提出的算法用于维护一组几何对象的组合几何结构。在这项工作中,我们提出一种方法,其中几何结构的计算是通过几何对象完成的,在本例中,计算是由机器人本身完成的。这与在动态数据结构框架中维护集中式数据结构不同。动力学自主机器人,每个都是计算对象,它们自己进行所有计算,并在树改变时更新生成树。就动态数据结构指标而言,我们的数据结构是本地且紧凑的。

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