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研究生:林亮均
研究生(外文):LIN LIANG-CHUN
論文名稱:結構光結合機械手臂重建工件三維模型之研究
論文名稱(外文):Three Dimensional Model Reconstruction Using Structured-light Scanner And Robotic Arm
指導教授:江佩如
指導教授(外文):CHIANG, PEI-JU
口試委員:江佩如陳世樂林榮信陳正倫
口試委員(外文):CHIANG, PEI-JUCHEN, SHYH-LEHLIN, RONG-SHINECHEN, CHENG-LUN
口試日期:2018-07-30
學位類別:碩士
校院名稱:國立中正大學
系所名稱:機械工程系研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:中文
論文頁數:81
中文關鍵詞:結構光機械手臂掃描組態最佳視角
外文關鍵詞:Structured light scannerrobotic armscanning gesture
相關次數:
  • 被引用被引用:1
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  • 下載下載:132
  • 收藏至我的研究室書目清單書目收藏:0
有鑒於文獻中常用來計算掃描組態的平整塊演算法(flat patch recursive algorithm)在掃描效率上的低落,本研究將影像分割常用的區域成長(Region Growing)概念,擴展於物體三維網格模型上計算出掃描組態,並且以七種物體模型進行模擬測試,之後整合結構光掃描系統、六軸機械手臂進行實際掃描並和文獻演算法進行比較,模擬及實驗結果顯示:本研究所提出的演算法隨著模型網格數增加,姿態數及耗費時間會漸漸少於文獻演算法,且整體涵蓋率相差不大,可有效縮短掃描時間並防止多視角點雲間定位誤差的累積。
The study integrates structure light system with six-axis manipulator
to examine the algorithm performance in different situation. Generally, based on the CAD model, flat patch recursive algorithm is used to calculate the scanning gestures for robot equipped with a 3D scanner. However, the required number of gestures calculated by flat patch recursive algorithm is significant for CAD model with huge number of meshes. To improve the efficiency of existing scanning gesture searching algorithm, this study expanded the concept of region growing which is commonly used in image segmentation to three-dimensional mesh model to calculate the potential scanning gestures. In this study, seven different objects with CAD models have been used to compare performance between the proposed algorithm and flat patch recursive algorithm. The experimental result shows that although the scanning area is a little bit less than the existing algorithm, the number of scanning gesture of proposed algorithm is significantly reduced and thus prevents accumulating error resulted from multiple view registration. In addition, the computation time of proposed algorithm is less than the one of flat patch recursive algorithm.

目錄
致謝 I
中文摘要 II
ABSTRACT III
目錄 IV
圖目錄 VII
表目錄 X
第1章 緒論 1
1.1. 研究動機與目的 1
1.2. 文獻回顧 2
1.2.1 手部相機的校正 2
1.2.2 掃描組態規劃演算法 4
1.2.3 多筆資料定位與整合 13
1.2.4總結 19
1.3. 章節提要 20
第2章 三維重建原理 21
2.1. 三維重建技術 21
2.2. 三角量測法 21
2.3. 結構光編碼 22
2.4. 三維資訊解碼與重建 25
第3章 六軸機械手臂建模與空間座標整合 26
3.1.連桿參數與座標 26
3.2. 機械手臂運動學 28
3.2.1 正向運動學 28
3.2.2 逆向運動學 31
3.3.手部相機的校正 40
第4章 重建工件三維模型 46
4.1. 掃描範圍定義 46
4.2. 種子成長法 48
4.3. 分離背景和雜訊 54
4.4.計算模型偏差 55
第5章 實驗與數據分析 56
5.1. 實驗設備 56
5.2. 實驗流程 60
5.2.1 結構光校正 60
5.2.2 手部相機校正 62
5.2.3 掃描組態產生 64
5.2.4 三維資訊處理 71
5.3. 實驗結果分析 76
第6章 結論與未來工作 77
6.1. 結論 77
6.2. 未來工作 77
參考文獻 79


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