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A fractal conductivity-based approach to mobile sensor networks in a potential field

机译:基于分形电导率的势场中移动传感器网络方法

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This paper presents the design of multi-robots or multiple mobile sensors and gives the results of the team behavior of them in a potential field in a collaborative manner. The aim is to prove the concept of the fractal conductivity-based approach to mobile sensor networks in a potential field. We attempted to create multi-robots having similar inherent nature, similar background knowledge, and the same mission as relevant bodies, the creation of some sort of attraction force between them is achieved with the application of fractal conductivity of belief functions. We attempted to develop multi-robots capable of carrying out an orchestrated movement in an environment having some kind of potential field such as a chemical substance contaminated into sea or lake water. The basis of the theory of behavior in a potential field is established. The fractal conductivity approach is explained. A mobile sensor structure having an input, output, and internal belief functions is designed. Internal structures of mobile sensors are implemented by software. A mobile sensor network composed of mobile sensor nodes is developed. Two communities of interest groups have been constituted. Collaborative behaviors of multi-robots in a potential field are investigated. The mobile sensors move towards a target by sensing the potential field at their locations, broadcasting the information composed of locally sensed intensity of the potential field around them and the infrastructure knowledge of themselves to other sensors and receiving the information of the potential field intensities together with the identity information that is being broadcasted from the other mobile sensors inside the potential field. The target is a source creating the potential field. A mobile sensor is a body incorporating a prior knowledge base that is the identity information in the form of a fractal belief function inside itself. After developing the theoretical basis for sensing potential field and movement, a fractal conductivity approach, which is based on fractal natures of the belief functions, is applied to this basic approach to obtain the movements of the multi-robots as a coordinated team, i.e., grouped as relevant bodies. The operation of mobile sensors based on time division multiple access method is achieved. The results of coordinated movement and obstacle avoidance have been demonstrated by the simulation results.
机译:本文介绍了多机器人或多个移动传感器的设计,并以协作的方式给出了它们在潜在领域的团队行为的结果。目的是证明在潜在领域中基于分形电导率的移动传感器网络方法的概念。我们试图创建具有相似的内在特性,相似的背景知识以及与相关机构相同的任务的多机器人,它们之间的某种吸引力的产生是通过使用信念函数的分形传导率来实现的。我们试图开发能够在具有某种潜在领域(例如被海水或湖水污染的化学物质)的环境中进行精心策划的运动的多功能机器人。建立了势场行为理论的基础。解释了分形电导率方法。设计了一种具有输入,输出和内部置信功能的移动传感器结构。移动传感器的内部结构由软件实现。开发了由移动传感器节点组成的移动传感器网络。组成了两个利益集团。研究了多机器人在潜在领域的协作行为。通过感测移动传感器在其位置处的势场,将由它们周围的势场的局部感测强度及其自身的基础结构知识组成的信息广播到其他传感器,并与其他传感器一起接收势场强度的信息,从而向目标移动从势场内其他移动传感器广播的身份信息。目标是创建电位场的源。移动传感器是结合了现有知识库的主体,该现有知识库是其内部以分形信念函数形式存在的身份信息。在建立了用于感测势场和运动的理论基础之后,基于信念函数的分形性质的分形电导率方法被应用于该基本方法,以获得作为协调团队的多机器人的运动,即,归类为相关机构。实现了基于时分多址方法的移动传感器的操作。仿真结果证明了协调运动和避开障碍物的结果。

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