光達（Light Detection And Ranging，LiDAR）量測為近年來備受重視且開始廣泛應用的一種探測技術，對於以 3D 方式呈現的視覺化系統因受到大眾青睞而迅速發展，對於進行三維重建技術而言，光達資料便具有相當的價值，能夠提供細緻的物面資訊，如房屋、車輛等物件特徵，運用彩色成像技術，建立起影像（Image）與雷射（Laser）技術間的橋梁，達成即時成像的效果，發揮光達技術的實用性。
本研究設計一套結合雷射測距儀（Laser Range Finder，LRF）與 3D 視覺化介面之掃瞄系統，並搭配位移感測器、慣性量測單元（Inertial Measurement Unit，IMU）進行方位推估，透過移動式載具的位移量與攝影機所擷取之環境色彩資訊，並藉由 2D 與 3D 間的座標轉換方法，即時得到相對應的三維座標資訊，完成三維點雲（Point Cloud）資料之蒐集，此環境資料量測蒐集方法，亦稱為車載移動測繪系統（Mobile Mapping System，MMS）。本研究之移動式測繪系統除具有多感測器整合與資料蒐集外，強調即時點雲顯示的效果，配合硬體與資料點間的記憶體轉移（Direct Memory Access，DMA）方法，讓三維點雲資料能夠快速地呈現到三維視覺平台，達到同步之功能。
本研究除了開發建圖系統外，也利用了點雲資料重建的概念，計算具有共面特性的點雲特徵，並分析點雲中的重建參數。其計算過程中，以點雲中的取樣點距離與角度做為判斷依據，以利進行相同平面的區域連結；此外，透過點雲重建與方位推估的校正方法，結合於實際比例尺之平面等高線地圖與 3D 點雲資訊結合，不僅能夠與點雲資料匹配以確認精度外，也構成「新地理學」所代表的 3D 地圖，使本研究成為一套完整獨立的移動式建圖系統。

Nowadays, LiDAR(Light Detection And Ranging, LiDAR) is the more important and widely applicable measurement technique. The rise of visual system in 3D is very useful to the measurement of LiDAR and gets more importance value for 3D reconstruction technology, in which abundant surface features are implied in the point cloud data. Combined with the image and laser technique for real-time rendering, the LiDAR will be more functional.
This thesis proposes and designs a system which combined with Laser Range Finder and 3D visual interface for vehicles, and also equipped with rotary encoder and initial measurement unit to DR(Dead Reckoning) function. Through the coordinate transform method of 2D to 3D, the 3D coordinate of each point will be calculated, and embedded with the color information which captured from the camera to take 3D color point cloud collection. This method is also called Mobile Mapping System(MMS). In addition, this mapping system uses Direct Memory Access technology to display the point cloud synchronous in 3D visual system.
Except for the point cloud collection, the reconstruction of point cloud data is used in this system. The surface reconstruction is based on Nearest Neighbor Interpolation method. There are two factors to conduct the interpolation process: the angle and distance between two sample points from the points sequence. The reconstruction of point cloud and calibration of DR is not only to confirm the accuracy of 3D point cloud map but also the “New Geography” of the 3D electronic map. This research will build up an independent Mobile Mapping System.

論文審定書 i
致謝 ii
中文摘要 iii
Abstract iv
第一章 緒論 1
1-1 研究動機 1
1-2 文獻回顧 2
1-3 主要貢獻 9
1-4 章節介紹 10
第二章 系統概述 11
2-1 系統簡介 11
2-2 系統功能 12
2-2-1 定向定位系統 12
2-2-2 定向與定位系統整合方法 12
2-2-3 即時資訊蒐集與儲存 18
2-2-4 三維視覺化系統 22
2-3 系統流程 24
2-4 硬體實現 27
第三章 座標系統 28
3-1 OpenGL三維繪圖座標系 28
3-2 雷射測距儀座標系 31
3-3 方位推估座標系與載體座標系 35
3-4 地球中心地球固定座標系 36
第四章 系統演算 41
4-1 直接定位方位推估法 41
4-2 大地座標轉換 42
4-3 點雲顏色匹配 48
4-4 最接近點內插法 49
4-5 平面地圖疊合 55
第五章 系統實現 57
5-1 實驗平台 57
5-2 感測器 58
5-2-1 雷射測距儀 58
5-2-2 光學編碼器 62
5-2-3 慣性量測單元 67
5-2-4 視覺系統 68
5-2-5 全球定位系統 69
5-3 傳輸模組 71
5-4 軟硬體系統 74
第六章 實驗結果 77
6-1 實驗場景 77
6-2 實驗流程 79
6-3 三維點雲圖像 83
6-4 彩色點雲圖像 84
6-5 內插法重建圖像 86
6-6 地圖疊合圖像 87
6-7 移動路徑規劃 89
第七章 結論與未來展望 91
7-1 結論 91
7-2 未來展望 92
參考文獻 94
附錄 100

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