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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/102553


    Title: 使用手機加速度計和陀螺儀之室內定位
    Other Titles: Indoor localization with accelerometer and gyroscope on smartphone
    Authors: 彭威然;Peng, Wei-Jan
    Contributors: 淡江大學資訊工程學系資訊網路與通訊碩士班
    許輝煌
    Keywords: 加速度計;陀螺儀;室內定位;行人航位推算;Accelerometer;Gyroscope;localization;PDR
    Date: 2014
    Issue Date: 2015-05-04 09:58:41 (UTC+8)
    Abstract: 在此研究中,我們希望可以做到以較低的成本和方便使用的方式來達到室內定位的效果。如今智慧型手機進步快速,戶外定位系統於手機上不再是新鮮的事情,但是如今的定位系統皆是使用衛星定位訊號來進行作業,在室內中使用並無法達到準確的效果,訊號會被建築物所遮蔽。因此我們希望藉此研究來做出一個使用其他方式來進行室內定位的系統。
    目前各種熱門公共場所都是許多觀光客常常會去的地方,例如地下街,各百貨公司。而這些地方通常都很大,第一次去的民眾大多會逛一逛之後,搞不清楚自己目前所在的位置而迷路。如此狀況下,如果有一套室內定位系統,讓使用者隨時可以知道自己目前所在的位置是一件很方便的事情,因此我們設計了一套在室內GPS訊號不準確的室內也可以使用的室內定位系統。為了使用上方便,我們建構在現在幾乎人人皆有的智慧型手機上面。我們希望使用低成本且方便的方式來達到室內定位的效果,因此排除了在環境內架設感應器來定位的方式,而採用PDR (Pedestrian Dead Reckoning) 的方式來進行行人航位推算,即是假設起始位置已知,再以使用者走路的步數,步伐大小和方向來進行目前所在位置的推算。使用者以手動方式輸入目前所在位當作起始點位置,使用了手機內建的感應器來蒐集使用者步行的資訊。我們以加速度感應器來蒐集使用者在行走中所產生的加速度,觀察行走時所產生的加速度特徵,以此來做為判斷行走步數的依據,並且評估目前現有的步幅計算方法,取較適合本研究中使用的方法來計算步幅的大小。以陀螺儀感應器在行人轉向時所產生的數值變化,計算出使用者轉向的角度,以此方式獲得行人行走的資訊,再搭配上適當的地圖來獲得最後定位的結果,則可以達到低成本且方便的室內定位效果。
    Many people get lost easily in public places if they are not familiar with the environment. It would be very helpful to have an indoor localization system. Many researches in indoor localization can be found in the literature. However, they usually need to deploy sensors in the environment. It is costly and inconvenient. In this research, we propose to develop a smartphone indoor positioning application based on accelerometer and gyroscope data. The PDR (Pedestrian Dead Reckoning) method is used to build this application. Calibration points are marked both on the floor ground and on the map of the application. The user first finds a calibration mark, stand on it and face the right direction. He/she then place the android icon (representing the user) on top of the calibration point. When he/she starts to move, the android icon also moves on the map following the real-time estimates of step length and orientation change for each step from accelerometer and gyroscope data, respectively. Preliminary results in walking distance and orientation estimation show high accuracy. The application seems promising and useful as long as a map and calibration marks are built in advance.
    Appears in Collections:[資訊工程學系暨研究所] 學位論文

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