{"title":"The Summary of Indoor Navigation Possibilities Considering Mobile Environment","authors":"László Kundra, P. Ekler","doi":"10.1109/ECBS-EERC.2013.32","DOIUrl":null,"url":null,"abstract":"Indoor navigation falls into two main categories: helping people to find their way in buildings, and for automation purposes for example for robots or quadricopters. In this paper pedestrian navigation is being discussed using commercial mobile phones in that particular case, when global navigation systems are not available. Furthermore no beacon or internet-based aid is applied. This type of indoor navigation is called offline indoor navigation, where the main concept is to use onboard sensors of mobile phones and apply different filtering solutions and algorithms for examples such algorithms that follows pedestrian movements. In this paper we compare different solutions for indoor navigation with real measurements. Therefore this work can be considered as a summary work for indoor navigation techniques. Furthermore we propose techniques and measurements for offline indoor navigation by applying different filters and noise processing algorithms considering the limitations of the sensors.","PeriodicalId":314029,"journal":{"name":"2013 3rd Eastern European Regional Conference on the Engineering of Computer Based Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 3rd Eastern European Regional Conference on the Engineering of Computer Based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECBS-EERC.2013.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Indoor navigation falls into two main categories: helping people to find their way in buildings, and for automation purposes for example for robots or quadricopters. In this paper pedestrian navigation is being discussed using commercial mobile phones in that particular case, when global navigation systems are not available. Furthermore no beacon or internet-based aid is applied. This type of indoor navigation is called offline indoor navigation, where the main concept is to use onboard sensors of mobile phones and apply different filtering solutions and algorithms for examples such algorithms that follows pedestrian movements. In this paper we compare different solutions for indoor navigation with real measurements. Therefore this work can be considered as a summary work for indoor navigation techniques. Furthermore we propose techniques and measurements for offline indoor navigation by applying different filters and noise processing algorithms considering the limitations of the sensors.