Scalable Distributed Protocol for Modular Micro-Robots Network Reorganization
Scalable Distributed Protocol for Modular Micro-Robots Network Reorganization
复制标题
用于模块化微型机器人网络重组的可扩展分布式协议
DOI：
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复制
发表时间：
2016
影响因子：
10.6
通讯作者：
J. Bourgeois
中科院分区：
文献类型：
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作者：
H. Mabed;J. Bourgeois
可编程材料是微机器人组网中最具挑战性的问题之一。除了毫米级移动设备小型化带来的问题外，允许大量机器人协调的分布式异步算法的概念仍然是一项非常复杂的任务。微型机器人网络代表了物联网的实现之一，其中一组微型机器人对在无线下行链路信道上提交的指定全球目标的命令做出反应。在变形问题的情况下，该目标对应于目标形状。可编程材料在可绘制显示、原型制作、运动等领域有着广泛的应用。本文提出了一种新颖的灵活的分布式算法，允许将模块化的微机器人网络重组成期望的目标形状(物理拓扑)。这种算法的效率是基于存储器需求、通信负载和为达到最终形状而执行的动作的数量来评估的。所提出的算法在可实现的目标形状的范围方面表现出很大的灵活性，部分原因是不需要对最终形状进行显式描述。为了评估所提算法的计算性能，我们提出了变形问题的线性规划模型，该模型提供了优化准则的下界。我们的结果与松弛线性规划的结果进行了比较，证明了我们方法的有效性。
The programmable material is one of the most challenging problems in micro-robot networking. In addition to the problems that arise by the miniaturization of millimeter-scale mobile devices, the conception of the distributed asynchronous algorithms allowing the coordination of large number of robots remains a very complex task. Micro-robot network represents one of the implementations of the Internet of things, where a set of micro-robots react to an order submitted on a wireless downlink channel specifying a global goal. This goal corresponds to a target shape in the case of shape-shifting problem. Programmable materials have many applications in the field of paintable displays, prototyping, locomotion, etc. We propose in this paper an original flexible distributed algorithm allowing to reorganize a modular micro-robot network into a desired target shape (physical topology). The efficiency of such an algorithm is assessed on the basis of the memory requirements, the communication load, and the number of performed movements to reach the final shape. The proposed algorithm shows a great flexibility concerning the range of target shapes that can be achieved, in part because there is no need for an explicit description of the final shape. To assess the computational performances of the presented algorithm, we proposed a linear programming model of the shape-shifting problem that provides a lower bound of optimized criteria. The comparison of our results with those given by the relaxed linear programming proves the efficiency of our approach.