Object level mapping of an indoor environment using RFID

Hemanth Malla, Preethish Purushothaman, Shivnesh V. Rajan, Vidhya Balasubramanian
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引用次数: 11

Abstract

Many of the indoor applications like navigation, indoor localization, object tracking require an indoor map. Indoor environments are dynamic in nature because of the objects present in it. To capture the essence of the indoor environment, it is essential to perform an object level mapping of an indoor space. This is because an object has the potential to alter the map of an indoor environment. Mapping a huge indoor environment could prove to be costly in terms of time with high infrastructure dependency. This compels us to find a simple solution in terms of cost, time and reliability to build an indoor map. The proposed solution should have minimal infrastructure dependence, so that it can be used in situations like disaster and rapid response scenarios, where the available infrastructure is minimal and time is of essence. We propose a Radio Frequency Identification(RFID) based approach which performs an object level mapping of the indoor environment using a portable RFID reader, RFID Ultra High Frequency(UHF) passive tags and inertial navigation sensors(INS). This approach identifies each object in the indoor environment using one or more passive tags. A novel algorithm has been developed which accurately maps the objects present in the indoor space. It is easily scalable to map huge indoor environments and can be applied without any intensive manual labor or expensive equipments. Our experiments show that this approach generates object level indoor maps with high accuracy.
使用RFID的室内环境的对象级映射
许多室内应用,如导航、室内定位、目标跟踪,都需要室内地图。室内环境在本质上是动态的,因为存在于其中的物体。为了捕捉室内环境的本质,对室内空间进行对象级映射是必不可少的。这是因为物体有可能改变室内环境的地图。绘制一个巨大的室内环境可能会被证明是昂贵的时间和高度依赖基础设施。这迫使我们在成本、时间和可靠性方面寻找一种简单的解决方案来构建室内地图。建议的解决方案应该具有最小的基础设施依赖,这样它就可以用于灾难和快速响应场景等情况,在这些情况下,可用的基础设施很少,时间很重要。我们提出了一种基于射频识别(RFID)的方法,该方法使用便携式RFID阅读器、RFID超高频(UHF)无源标签和惯性导航传感器(INS)对室内环境进行对象级映射。这种方法使用一个或多个被动标签识别室内环境中的每个物体。开发了一种新的算法,可以准确地映射室内空间中的物体。它可以很容易地扩展到绘制巨大的室内环境,并且不需要任何密集的人工劳动或昂贵的设备。实验表明,该方法生成的物体级室内地图具有较高的精度。
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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