Multilevel localization for Mobile Sensor Network platforms

Jae-Young Park, H. Song
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引用次数: 15

Abstract

For a set of mobile sensor network, a precise localization is required in order to maximize the utilization of mobile sensor network. As well, mobile robots also need a precise localization mechanism for the same reason. In this paper, we showed a combination of various localization mechanisms. Localization can be classified in three big categories: long distance localization with low accuracy, medium distance localization with medium accuracy, and short distance localization with high accuracy. In order to present localization methods, traditional map building technologies such as grid maps or topological maps can be used. We implemented mobile sensor vehicles and composed mobile sensor network with them. Each mobile sensor vehicles act as a mobile sensor node with the facilities such as autonomous driving, obstacle detection and avoidance, map building, communication via wireless network, image processing and extensibility of multiple heterogeneous sensors. For localization, each mobile sensor vehicle has abilities of the location awareness by mobility trajectory based localization, RSSI based localization and computer vision based localization. With this set of mobile sensor network, we have the possibility to demonstrate various localization mechanisms and their effectiveness. In this paper, the preliminary result of sensor mobility trail based localization and RSSI based localization will be presented.
移动传感器网络平台的多级定位
对于一组移动传感器网络,为了最大限度地利用移动传感器网络,需要精确定位。同样,移动机器人也需要精确的定位机制。在本文中,我们展示了多种定位机制的组合。定位可以分为三大类:低精度的远距离定位、中等精度的中距离定位和高精度的短距离定位。为了呈现定位方法,可以使用传统的地图构建技术,如网格地图或拓扑图。我们实现了移动传感器车辆,并利用它们组成了移动传感器网络。每辆移动传感器车都是一个移动传感器节点,具有自动驾驶、障碍物检测与避障、地图构建、无线网络通信、图像处理以及多个异构传感器的可扩展性等功能。对于定位,每个移动传感器车辆都具有基于移动轨迹定位、基于RSSI定位和基于计算机视觉定位的位置感知能力。有了这套移动传感器网络,我们就有可能展示各种定位机制及其有效性。本文将介绍基于传感器移动轨迹的定位和基于RSSI的定位的初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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