整合 VI – SLAM 與 BLE 定位之 BIM 現地呈現擴增實境系統｜國立臺灣科技大學博碩士論文系統

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研究生：	陳志榮 Jhih-Rong Chen
論文名稱：	整合 VI – SLAM 與 BLE 定位之 BIM 現地呈現擴增實境系統 System development of an Augmented Reality on-site BIM viewer based on the integration of VI-SLAM and BLE indoor positioning
指導教授：	陳鴻銘 Hung-Ming Chen
口試委員:	謝佑明莊子毅
學位類別：	碩士 Master
系所名稱：	工程學院 - 營建工程系 Department of Civil and Construction Engineering
論文出版年：	2020
畢業學年度：	108
語文別：	中文
論文頁數：	109
中文關鍵詞：	擴增實境、物聯網、建築資訊模型、即時定位與地圖建構
外文關鍵詞：	Augmented reality, Internet of things, Building Information Modeling, Simultaneous localization and mapping
相關次數：	點閱：339 下載：0
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傳統上，在營建領域中，如須於現場檢視 BIM (Building Information Model，BIM)模型，一般是將平板電腦或是筆記型電腦等裝置攜帶於現場並藉由相關的視覺化檢視軟體進行模型檢視，而透過電腦觀看模型不易與現場真實所見情境進行結合，本研究計畫使用擴增實境(Augmented Reality，AR)將現場與 BIM 模型進行更即時且直觀的虛實整合呈現。近年來，擴增實境(Augmented Reality，AR)相關的視覺化技術不斷的發展，現今多數使用的無標記式或稱弱標記式圖像識別，是使用物體本身影像的特徵點作為識別物呈現虛擬內容，若是裝置相機中失去識別圖像時將導致擴增實境功能無法預期呈現。故本研究導入基於即時定位與地圖建構（Simultaneous Localization and Mapping，SLAM）的擴增實境呈現方式，透過裝置對於空間的認知進行 BIM 模型的擺放而後將模型於現地中與真實物件進行疊和，並結合室內定位技術，即時定位出使用者所在房間並載入屬於該房間的模型。此外，本系統也將導入物聯網(Internet of Things, IoT)環境監測系統，同步的以擴增實境進行視覺化呈現使用者所在房間配置的感測器即時資訊。一般而言，建築與物聯網模型及所含數據與擴增實境中點雲資訊相當大量與複雜，難以直接進行視覺化呈現，故須探討一種可行的方式，將模型、數據與點雲資訊儲存於伺服器中，並與程式執行期間藉由網路傳輸載入使用者裝置中進行擴增實境呈現。

Traditionally, when an engineer wants to use BIM on-site to support tasks for construction or maintenance, the common approach is to use a tablet or a notebook to run the BIM viewer on the site. In such manner, manual operation for model manipulation is required. In addition, the BIM presented through the screen and the actual on-site scene are in two separated view, thus the two is less likely to be synchronized and combine. Augmented Reality (AR) is a technology which superimposes virtual objects or information on the real world images or videos for interaction. Therefore, this study applied AR to superimpose BIM with the view of real site in indoor environment for presenting a more immediate and intuitive integration of the two. In present, most of the applications of combining BIM with AR uses marker or marker-less image recognition to superimpose virtual content using feature points of the marker or object image as an identifier. If the identifier moves outside the device camera view, the virtual content will not appear is such AR mode. With the advance of AR, this research introduces a new AR mode based on Simultaneous Localization and Mapping (SLAM). Based on this technology, the virtual BIM is placed based on the device understanding of the environment and then superimposed on the real objects in the scene without any identifier. This research proposes a manual method to align a chosen BIM component to a corresponding real object. Based on the alignment, the system calculates the angle and position to accurately place the BIM in the virtual environment for superimposing and records them for future use. Since the load and display of a whole BIM is not necessary and inefficient in the context of indoor AR applications, a BIM is divided into room models, and the system only overlays the corresponding room model in each specific room. This is achieved by combining with the BLE indoor positioning technology, so that the room which user is located can be immediately identified and the corresponding room model is loaded.

論文摘要            I
ABSTRACT    II
目錄            III
圖目錄            V
表目錄            VIII
第1章、    緒論                                   1
1    研究背景與動機                           1
2    研究目的                                   7
3    研究範圍                                   10
4    研究方法                                   10
5    論文架構                                   11
第2章、    文獻回顧                                   12
1    相關研究發展                           12
1.1    擴增實境定義                           12
1.2    擴增實境技術發展                           13
1.3    無標記擴增實境與相關定位的應用與發展       15
2    系統開發工具與技術                       22
2.1    系統平台                                   22
2.1.1    基於 VI-SLAM 的 AR SDK                   22
2.1.2    Unity3D                                   23
2.2    雲端技術                                   24
2.2.1    HDFS (Hadoop Distributed File System)  24
2.2.2    Apache Hbase                           24
2.2.3    Apache Thrift                          26
2.2.4    Apache HTTP Server                     27
2.2.5    PHP                                   27
2.3    物聯網                                   27
2.3.1    Arduino                                   28
2.3.2    無線感測網路                           29
2.3.3    室內定位技術                           30
2.3.4    BLE低功耗藍芽                           32
2.3.5    Eddystone通訊格式                       33
2.3.6    RedBearLab BLE Shield                  35
第3章、    系統架構與運作機制                       36
1    系統架構                                   36
1.1    系統前置作業                           36
1.1.1    數據處理                                   37
1.1.2    模型處理                                   38
1.1.3    AR前處理系統                            39
1.2    系統運作流程                           40
1.2.1    室內定位運作流程                           41
1.2.2    貼合運作流程                           42
1.2.3    AR呈現流程                           43
2    系統運作機制                           44
2.1    BIM模型處理                           44
2.1.1    Autodesk Revit 模型切割                   45
2.1.2    Autodesk 3D Studio Max材質處理           46
2.1.3    Unity3D 房間分割與轉檔                   49
2.1.4    BIM元件資訊匯入資料庫                   49
2.2    物聯網室內監控感測器組架設                   52
2.2.1    Arduino (資料發送端)                   53
2.2.2    Respberry Pi (資料接收端)           54
2.2.3    ZigBee 網路                           56
2.2.4    BLE定位機制                           57
2.3    AR前處理系統                           58
2.3.1    房間掃描機制                           58
2.3.2    模型放置機制                           60
2.3.3    模型貼合位置紀錄機制                   62
2.4    HBase 資料庫配置                           65
2.5    輔助工具                                   69
2.5.1    IOT 於AR 視覺化呈現                   69
2.5.2    地圖即時位置導覽                           71
第4章、    系統效能驗證                           73
1    程式執行效能                           73
2    BLE 房間定位驗證                           74
3    模型貼合程度與穩定性                   78
第5章、    結論與未來展望                       81
1    結論                             81
2    未來展望                           82
第6章、    參考文獻                           83

                                

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全文公開日期 2025/06/11 (校內網路)
全文公開日期 2025/06/11 (校外網路)
全文公開日期 2025/06/11 (國家圖書館：臺灣博碩士論文系統)

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