多机器人探索的泛洪算法。

Flavio Cabrera-Mora, Jizhong Xiao
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引用次数: 19

摘要

在本文中,我们提出了一种多机器人探索算法,旨在通过协调进行探索的机器人的运动来减少机器人的探索时间和最小化机器人的总穿越距离。将环境建模为树,我们考虑一个协调模型,该模型限制了在每一步中允许遍历边缘和进入顶点的机器人数量。这种协调是通过机器人使用一组活动地标以分散的方式实现的,这些地标由它们在探索的顶点上丢弃。对该算法在树上进行了数学分析,得到了该算法的主要性质,并确定了其在探索时间上的界限。我们还定义了多机器人算法的三个性能指标。我们将这种新算法的性能与我们在最近的论文中提出的多机器人深度优先搜索(MR-DFS)方法和经典的单机器人深度优先搜索方法进行了仿真和比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A flooding algorithm for multirobot exploration.

In this paper, we present a multirobot exploration algorithm that aims at reducing the exploration time and to minimize the overall traverse distance of the robots by coordinating the movement of the robots performing the exploration. Modeling the environment as a tree, we consider a coordination model that restricts the number of robots allowed to traverse an edge and to enter a vertex during each step. This coordination is achieved in a decentralized manner by the robots using a set of active landmarks that are dropped by them at explored vertices. We mathematically analyze the algorithm on trees, obtaining its main properties and specifying its bounds on the exploration time. We also define three metrics of performance for multirobot algorithms. We simulate and compare the performance of this new algorithm with those of our multirobot depth first search (MR-DFS) approach presented in our recent paper and classic single-robot DFS.

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