七自由度冗餘機械手臂之隨機物體的吸取姿態規劃

機構典藏 > College of Engineering > Graduate Institute & Department of Electrical Engineering > Thesis > Item 987654321/114772

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Title:	七自由度冗餘機械手臂之隨機物體的吸取姿態規劃
Other Titles:	Drawing posture planning of random objects for 7-DOF redundant robot manipulator
Authors:	陳湘筠;Chen, Hsiang-Yun
Contributors:	淡江大學電機工程學系碩士班翁慶昌;Wong, Ching-Chang
Keywords:	Kinematics;Null Space;Point Cloud;Posture Planning;Redundant Robot Manipulator;冗餘機械手臂;姿態規劃;運動學;零空間;點雲
Date:	2017
Issue Date:	2018-08-03 15:03:35 (UTC+8)
Abstract:	本論文之主要目的在於設計與實現一個七自由度冗餘機械手臂以及一個具有RGB-D攝影機的視覺系統，讓機械手臂可以在不指定特定目標位置的狀態下，自主完成吸取物件的任務。主要有三個主題：(1) 七自由度冗餘機械手臂的設計、(2) 冗餘度機械手臂的運動控制、以及(3) 隨機物體的吸取姿態規劃。在七自由度冗餘機械手臂的設計上，為了讓機械手臂達成更高的靈活度，本論文設計之機械手臂具有冗餘度，其可達成避免空間限制及增加機械手臂工作範圍的目的。在冗餘度機械手臂的運動控制上，由於七自由度冗餘機械手臂在逆向運動學上具有無限多組解，因此需要額外增加一個冗餘度限制來確定逆向運動學的唯一解，本論文主要採用運動學解耦合的方式來計算。在隨機物體的吸取姿態規劃上，本論文採用RGB-D攝影機來擷取物件之點雲資料，並且用點雲資料庫來分割真實影像的色彩點雲資料，以找出物體的姿態，然後決定手臂吸取物體時的姿態。在實驗結果方面，本論文利用自行開發之七自由度冗餘度機械手臂來實現運動控制方法，並完成一些模擬及實驗結果來說明所提出之運動控制方法確實可以讓機械手臂有不錯的控制成效。此外，本論文所提出之隨機物體的吸取姿態規劃不僅能成功辨識場景中的物體，且對於物體的平移及旋轉都能精準估測姿態。最後，一些結合所提出之運動控制與吸取姿態規劃的實驗結果，說明其確實可以讓七自由度冗餘機械手臂進行隨機物體的吸取任務。 The main purpose of this thesis is to design and implement a 7-DOF redundant robot manipulator and a vision system with a RGB-D camera so that the robot manipulator can draws objects automatically without specify a specific target location. There are three main themes: (1) design of the 7-DOF redundant robot manipulator, (2) motion control of the 7-DOF redundant robot manipulator, and (3) drawing posture planning of random objects. In the design of the 7-DOF redundant robot manipulator, a mechanism of robot manipulator with redundancy is designed to have a higher flexibility, which can achieve the purpose of avoiding space limitation and increasing the working space of the robot manipulator. In the motion control of the 7-DOF redundant robot manipulator, an additional redundancy parameter is needed to determine the unique solution of the inverse kinematics since the 7-DOF redundant robot manipulator has an infinite number of solutions in the inverse kinematics. This thesis mainly uses kinematics decoupling to find the unique solution. In the drawing posture planning of random objects, the RGB-D camera is used to capture the cloud data of objects and point cloud library (PCL) is used to segment the color point cloud data of the real image to find the posture of the object and then determine the drawing posture of this object. In the experimental results, the motion control of the 7-DOF redundant robot manipulator is implemented, and some simulation and experimental results are presented to show that the proposed motion control method does allow the robot manipulator to have a good control effect. In addition, the proposed drawing posture planning not only can successfully identify the objects in the scene, but can accurately estimate the posture of translation and rotation of the object. Finally, some experimental results by combining the proposed motion control method and the drawing posture planning illustrate that it can really let the implemented 7-DOF redundant robot manipulator carry out the task of random object drawing.
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Thesis

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