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首页> 外文期刊>IEEE transactions on industrial informatics >Multiagent Gathering With Collision Avoidance and a Minimax Distance Criterion—Efficient Algorithms and Hardware Realization
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Multiagent Gathering With Collision Avoidance and a Minimax Distance Criterion—Efficient Algorithms and Hardware Realization

机译：避免冲突和最小最大距离准则的多主体聚集—高效算法和硬件实现

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摘要

Multiple autonomous agents working cooperatively have contributed to the development of robust large-scale systems. While substantial work has been done in manufacturing and domestic environments, a key consideration for small hardware agents engaged in collaborative factory automation and welfare support systems is limited area and power on-board. When the agents attempt to meet for performing a task, it is natural for them to encounter obstacles and it is desirable for each agent to optimize its resources during its navigation. In this paper, we develop efficient geometric algorithms to find a point, termed as the gathering point (and denoted by P-G), for the agents that minimizes the maximum of path lengths. In particular, we present an O(n log(2) n) time algorithm for calculation of P-G for an environment with two agents and n static polygonal obstacles. We then use the notion of a weighted minimax point to derive an efficient algorithm (with complexity of O(k(2) + kn log(2) n)) for computing PG for an environment with k agents and n obstacles. An enhancement to a dynamic environment is then presented. We also present details of an efficient hardware realization of the algorithms. Each agent, equipped with only an ATmega328P microcontroller and no external memory, executes the algorithms. Experiments with multiple agents navigating amidst static as well as dynamic obstacles are reported.
机译：多个自治代理共同合作为强大的大型系统的开发做出了贡献。尽管在制造和家庭环境中已经进行了大量工作，但是参与协作工厂自动化和福利支持系统的小型硬件代理商的主要考虑因素是有限的面积和车载电源。当代理试图见面以执行任务时，他们自然会遇到障碍，并且希望每个代理在其导航期间优化其资源。在本文中，我们开发了有效的几何算法来找到一个点，该点称为代理的聚集点（并用P-G表示），以最小化最大路径长度。特别是，我们提出了一种O（n log（2）n）时间算法，用于计算具有两个代理和n个静态多边形障碍的环境的P-G。然后，我们使用加权的极大极小点的概念来推导一种高效算法（复杂度为O（k（2）+ kn log（2）n）），用于计算具有k个代理和n个障碍物的环境的PG。然后提出了对动态环境的增强。我们还将介绍算法的高效硬件实现的细节。每个代理程序仅配备一个ATmega328P微控制器，而没有外部存储器，它们执行算法。报告了在动态和静态障碍中使用多种智能体进行导航的实验。

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