本論文之主旨在設計一移動式機械臂的抓物控制系統。藉由安裝於機器人頭部之立體攝影機擷取影像資訊，使機器人得以在環境中找尋目標物體，並自主導引機器手臂至適當的抓取位置，完成抓取之動作。本文採用加速強健特徵點演算法(Speed up robust feature, SURF)來定義目標物體的特徵點，並且藉由比對當前畫面中的特徵點來判斷目標物是否存在於影像中。為了強化特徵比對結果並算出抓物控制所需的參考點，本論文採用隨機取樣篩選演算法(RANdom Sample Consensus, RANSAC)來估測平面轉換矩陣(Homography matrix)以準確的標出目標物的中心點。本論文並發展出一套座標估測的校正法，提高對於目標物座標估測之準確度。在影像伺服的控制設計上，針對機械手臂及移動平台設計了以座標估測結果產生控制命令的控制方法，導引移動式機械臂自主抓物。在本論文中，以實驗室自行設計的多自由度雙臂機器人搭配全向式移動平台，並裝置立體攝影機作為影像資訊輸入，驗證整套方法的可行性。經過實驗驗證，此系統可以導引機器人順利的移動並拿取所設定的目標物。

The objective of this study is to design a grasping system for a mobile manipulator, such that it can find and grasp a target in the environment. Speed up robust feature (SURF) algorithm is used to define the feature of a target object and to match features between current image and object database to confirm the target. To strengthen the feature matching results and calculate the necessary reference control point, we adopt RANSAC(RANdom Sample Consensus) algorithm to estimate the planar transformation matrix (homography matrix) in order to accurately mark the center of target. A set of coordinate estimation correction method is developed to improve the accuracy of target location estimation. A control design is developed based on coordinate estimation for the mobile manipulator for visual servoing for object grasping. Experiments on an self-constructed mobile manipulator reveal that the proposed method can find and grasp a target object successfully.

摘要 i
ABSTRACT i
誌謝 i
目錄 i
圖目錄 i
第一章 緒論 1
1.1 研究動機 1
1.2 相關研究 1
1.3 問題描述 5
1.4 系統架構 6
1.5 章節說明 7
第二章目標物辨識 8
2.1 特徵點擷取 9
2.1.1. SURF工作原理 9
2.1.2. 影像特徵點比對 13
2.2 錯誤比對剔除 14
2.2.1. Homography 14
2.2.2. RANSAC 16
2.3 定義中心點 19
第三章目標物姿態估測 21
3.1 立體視覺原理 21
3.2 3D座標公式校正 23
3.2.1. Z軸座標值估測 24
3.2.2. X軸座標值估測 28
3.2.3. Y軸座標值估測 32
3.3 三軸旋轉角 36
第四章移動式機械臂之影像伺服控制設計 39
4.1 手臂控制 39
4.1.1. 硬體構造 39
4.1.2. 座標轉換 39
4.1.3. 手腕逆運動學推導 44
4.1.4. 從假定腕部點逼近實際腕部點的方法 46
4.1.5. 抓取動作路徑規劃 48
4.2 移動平台控制 49
4.2.1. 硬體構造 49
4.2.2. 平台運動模型 51
4.2.3. 姿態估測 (Odometry) 54
4.2.4. 平台之運動控制 55
4.3 影像伺服控制 57
4.3.1. 視覺伺服控制架構 57
4.3.2. 控制設計 58
第五章實驗結果 62
5.1 實驗用機器人構造 62
5.2 平台靜止抓取實驗 65
5.3 平台移動抓取實驗 69
第六章結論與未來展望 74
6.1 結論 74
6.2 未來展望 74
參考文獻 76

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