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Localization and tracking algorithm for mobile robot based on wireless sensor network

机译:基于无线传感器网络的移动机器人定位与跟踪算法

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摘要

Purpose - The purpose of this paper is to describe a low-cost mobile robot localization and navigation system based on wireless sensor network (WSN). This can be used in extreme environments such as mines, hostile areas, and other places where static nodes cannot be deployed directly. Design/methodology/approach - The distance between robot and beacon nodes is estimated by received signal strength indicator (RSSI). The adaptive Kalman filter algorithm is used to eliminate noise from the RSSI signal. Then, the paper gets the mobile robot's status information which includes position, velocity, and acceleration. In order to improve the real-time performance of systems and reduce the computation overhead of robot's CPU, the paper chooses a beacon node by some certain rules to implement the localization program. The robot and beacon nodes use the CC2430 as the communication and data-processing unit. Findings - The experiment shows it has the characteristics of good position precision, is easily realized, and inexpensive. Research limitations/implications - That the system needs so many beacon nodes, is the main limitation. Practical implications - A very useful and low-cost method for mobile robot localization and navigation. Originality/value - The innovative aspect of the paper is that it attempts an analysis of the localization system based on WSN, by attempting to analyze and explain the model of localization system which includes robot and beacon nodes.
机译:目的-本文的目的是描述一种基于无线传感器网络(WSN)的低成本移动机器人定位和导航系统。它可以用于极端环境,例如矿山,敌对地区以及无法直接部署静态节点的其他地方。设计/方法/方法-机器人和信标节点之间的距离由接收信号强度指示器(RSSI)估算。自适应卡尔曼滤波器算法用于消除RSSI信号中的噪声。然后,纸张获得移动机器人的状态信息,包括位置,速度和加速度。为了提高系统的实时性能并减少机器人CPU的计算开销,本文通过一定的规则选择信标节点来实现定位程序。机械手和信标节点将CC2430用作通信和数据处理单元。发现-实验表明它具有良好的定位精度,易于实现且价格便宜的特点。研究局限性/含义-系统需要那么多信标节点是主要限制。实际意义-一种非常有用且低成本的移动机器人定位和导航方法。原创性/价值-本文的创新之处在于它试图通过分析和解释包括机器人和信标节点的定位系统模型来尝试分析基于WSN的定位系统。

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