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基于增强现实的室内导航系统。

ARBIN: Augmented Reality Based Indoor Navigation System.

机构信息

Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan.

National Taiwan University Hospital YunLin Branch, Yunlin 640203, Taiwan.

出版信息

Sensors (Basel). 2020 Oct 17;20(20):5890. doi: 10.3390/s20205890.

DOI:10.3390/s20205890
PMID:33080918
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7589552/
Abstract

Due to the popularity of indoor positioning technology, indoor navigation applications have been deployed in large buildings, such as hospitals, airports, and train stations, to guide visitors to their destinations. A commonly-used user interface, shown on smartphones, is a 2D floor map with a route to the destination. The navigation instructions, such as turn left, turn right, and go straight, pop up on the screen when users come to an intersection. However, owing to the restrictions of a 2D navigation map, users may face mental pressure and get confused while they are making a connection between the real environment and the 2D navigation map before moving forward. For this reason, we developed ARBIN, an augmented reality-based navigation system, which posts navigation instructions on the screen of real-world environments for ease of use. Thus, there is no need for users to make a connection between the navigation instructions and the real-world environment. In order to evaluate the applicability of ARBIN, a series of experiments were conducted in the outpatient area of the National Taiwan University Hospital YunLin Branch, which is nearly 1800 m, with 35 destinations and points of interests, such as a cardiovascular clinic, x-ray examination room, pharmacy, and so on. Four different types of smartphone were adopted for evaluation. Our results show that ARBIN can achieve 3 to 5 m accuracy, and provide users with correct instructions on their way to the destinations. ARBIN proved to be a practical solution for indoor navigation, especially for large buildings.

摘要

由于室内定位技术的普及,室内导航应用已在大型建筑物中部署,例如医院、机场和火车站,以引导访客到达目的地。智能手机上常用的用户界面是带有到达目的地路线的 2D 楼层地图。当用户到达交叉口时,导航指令(例如左转、右转和直走)会在屏幕上弹出。然而,由于 2D 导航地图的限制,用户在前进之前可能会面临将真实环境与 2D 导航地图联系起来的心理压力和困惑。出于这个原因,我们开发了基于增强现实的导航系统 ARBIN,它将导航指令发布在真实环境的屏幕上,便于使用。因此,用户无需在导航指令和真实环境之间建立联系。为了评估 ARBIN 的适用性,我们在国立台湾大学云林分院的门诊区进行了一系列实验,该门诊区面积近 1800 米,有 35 个目的地和兴趣点,例如心血管诊所、X光检查室、药房等。我们采用了四种不同类型的智能手机进行评估。我们的结果表明,ARBIN 可以达到 3 到 5 米的精度,并为用户提供前往目的地的正确指令。ARBIN 被证明是室内导航的实用解决方案,尤其是对于大型建筑物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/4d70d39b3fb6/sensors-20-05890-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/25ce5f6a71e8/sensors-20-05890-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/60c4e8b40860/sensors-20-05890-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/90a881fe636c/sensors-20-05890-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/97fd6ead5dc2/sensors-20-05890-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/1224588cf825/sensors-20-05890-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/ee13017131c9/sensors-20-05890-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/ffd5f11f37c3/sensors-20-05890-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/1636c735935a/sensors-20-05890-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/3443b0b00115/sensors-20-05890-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/9fb08562ce2d/sensors-20-05890-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/c025bfdb2055/sensors-20-05890-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/12b322fc9fe3/sensors-20-05890-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/4d70d39b3fb6/sensors-20-05890-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/25ce5f6a71e8/sensors-20-05890-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/d2fc65770a65/sensors-20-05890-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/4362eb1ed239/sensors-20-05890-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/60c4e8b40860/sensors-20-05890-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/90a881fe636c/sensors-20-05890-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/97fd6ead5dc2/sensors-20-05890-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/1224588cf825/sensors-20-05890-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/ee13017131c9/sensors-20-05890-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/ffd5f11f37c3/sensors-20-05890-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/1636c735935a/sensors-20-05890-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/3443b0b00115/sensors-20-05890-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/9fb08562ce2d/sensors-20-05890-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/c025bfdb2055/sensors-20-05890-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/12b322fc9fe3/sensors-20-05890-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36fd/7589552/4d70d39b3fb6/sensors-20-05890-g015.jpg

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