臺灣博碩士論文加值系統

本文旨在使用眼在手之影像系統辨識及定位三維工作空間之物體，並以機械臂影像回授控制完成視覺對正以及物體之抓取與放置等任務。發展之眼在手視覺對正系統之具體內容計有: (1)彩色影像顏色分割並據此偵測三維空間中物體之外形輪廓以及相機與物體之距離與方位角；(2)整合眼在手視覺系統與機械臂反運動學計算達到機械臂影像回授以及(3)計算物體影像特徵以及估測物體於三維空間之姿態並對正目標物體。最後，整合上述之機械臂、平動夾爪和眼在手視覺系統並基於電腦視覺回授完成三維空間物體辨識、量測以及抓取與放置等任務。實驗結果驗證本文所設計之機械臂及影像整合系統的正確性與有效性，整體物體對位控制之位置誤差小於1.2 mm以及角度誤差小於1.5度。

This paper aims to use the eye-in-hand vision system to identify and locate 3D objects in the work space, and the robotic system applies vision feedback control to execute tasks such as visual alignment as well as picking-and-placing objects. The specific functions of the developed vision alignment and control system are as follow: (1) performing color segmentation to obtain effective object segmentation results and to detect the contour of object and the distance and orientation between camera and object; (2) integrating eye-in-hand system and robot inverse kinematics calculation to achieve image feedback control and (3) computing the image feature of the object, estimating the posture of the object in the 3-dimensional space and aligning the target object. Finally, this work integrates the aforementioned robotic arm, flat gripper and eye-in-hand camera system and applies computer vision techniques to perform object identification, measurement, and picking-and-placing tasks. The experimental results have verified the correctness and validity of the proposed robot and vision integrated system with an overall alignment control error of 1.2 mm in positioning and 1.5 degrees in orientation angle.

摘要 I
Abstract II
誌謝 III
目錄 IV
圖表索引 VII
第一章 緒論 1
1.1 研究動機 1
1.2 文獻回顧 1
1.3 論文大綱 2
1.4 系統架構 2
第二章 物體影像辨識 3
2.1 顏色色彩空間 3
2.1.1 RGB色彩空間 3
2.1.2 HSV色彩空間 4
2.1.3 色彩空間 5
2.1.4 CIE Lab 色彩空間 5
2.2 色彩分割 7
2.2.1 色彩空間門檻值 8
2.2.2 最近鄰居分類法 10
2.3 物體形狀辨識 13
第三章 眼在手系統 15
3.1 機械臂系統 15
3.2 眼在手系統 15
3.3 相機成像 16
3.3.1 相機矩陣 16
3.3.2 相機校正 18
3.4 基於三維空間的物體座標計算 19
3.4.1 眼在手系統實現極線幾何 19
3.4.2 已知物體的特徵點的物體座標計算 21
第四章 視覺對正 25
4.1 影像特徵值 25
4.1.1 x軸與y軸偏移量之影像特徵值 26
4.1.2 z軸偏移量之影像特徵值 27
4.1.3 x軸與y軸旋轉量之影像特徵值 28
4.1.3 z軸旋轉量之影像特徵值 30
4.2 影像Jacobian矩陣 31
4.3 控制系統穩定性分析 33
4.3.1 目標物平移 33
4.3.2 目標物旋轉 34
4.4 系統動作決策 37
第五章 實驗結果 40
5.1 物體影像辨識實驗 40
5.2球心位置估算實驗 42
5.3 視覺對正實驗 43
5.4 單眼視覺深度量測實驗 47
5.5 物體夾取與放置實驗 51
5.6 相關論文比較 54
第六章 結論與建議 55
6.1 結論 55
6.2 建議 55
參考文獻 56

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