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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 連豊力(Feng-Li Lian) | |
| dc.contributor.author | Po-Yu Lin | en |
| dc.contributor.author | 林柏佑 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:07:15Z | - |
| dc.date.available | 2022-01-17 | |
| dc.date.available | 2022-11-24T03:07:15Z | - |
| dc.date.copyright | 2022-01-17 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-11-09 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80467 | - |
| dc.description.abstract | 在機械加工與製造自動化中，機械手臂扮演著關鍵的角色。最近，越來越多高重複性及危險的任務已經改由機械手臂來完成。然而，現今的機械手臂自動化加工系統仍然不夠靈活與強健，因為它們無法處理周遭的變化且受限於預訂條件。此外，還需要耗費大量的時間與額外的成本在事先定義工件上料的路徑與設計工件料盤等前置作業上。 本論文提出了一個配備深度相機的雙手臂機器人物件定位系統，用於自動化工件上料的程序，以提高機器人加工系統的靈活性與強健性。此系統能自動定位工件，然後透過將夾爪爪片插入夾持位置來上料。首先，根據點對特徵，藉由提出的基於標誌物多視角姿態估測方法來估測受到機器人夾爪遮蔽的被夾持工件的六維姿態，該方法在標誌物的協助下進行最佳視角規劃，從多個視角來獲取更多與工件相關的資訊以進行姿態估測。根據姿態估測的結果，考量方向限制生成一組定位被夾持工件抓取位置的雙臂姿態，並透過基於採樣的規劃演算法在線規劃達到該姿態的雙臂運動。然而，由於系統建模誤差與姿態估測誤差等等的誤差因素，可能存在定位誤差導致上料失敗。因此，本論文開發了一種物體定位控制策略來補償定位誤差。 最後，透過進行模擬和實驗，分析所得到的結果來評估所提出方法的性能並驗證所提出系統的可行性。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:07:15Z (GMT). No. of bitstreams: 1 U0001-0411202116455800.pdf: 15418618 bytes, checksum: 29e6ad436b3a6c6ddc6548749e2bb90b (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 摘要 iii ABSTRACT v CONTENTS vii LIST OF FIGURES ix LIST OF TABLES xvi Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Formulation 10 1.2.1 In-hand Object Pose Estimation 11 1.2.2 Dual-arm Motion Planning 12 1.2.3 Object-locating Control Strategy Design 13 1.3 Contributions 14 1.4 Organization of the Thesis 15 Chapter 2 Background and Literature Survey 17 2.1 Dual-/Multi-arm Robot for Manufacturing 17 2.2 View Planning 23 2.3 In-hand Object Pose Estimation 28 Chapter 3 Related Algorithms 32 3.1 Pinhole Camera Model 32 3.2 Hand-eye Calibration 35 3.3 Base Frame Calibration 40 3.4 Octomap 44 Chapter 4 System Overview 47 4.1 Coordinate Systems 47 4.2 System Architecture 49 Chapter 5 Marker-based Multi-view Object Pose Estimation 53 5.1 Workflow 54 5.2 Marker-based Next-best View Planning Strategy 56 5.2.1 Generation of Candidate Views 56 5.2.2 Simulation of Visual Perception 58 5.2.3 Selection of Next-best View 59 5.3 Data Processing 60 5.3.1 Point Cloud Segmentation 60 5.3.2 Surface Normal Estimation 61 5.4 6D Object Pose Estimation 63 5.4.1 Point Pair Feature Extraction 63 5.4.2 Hash Map Construction 64 5.4.3 Object Pose Hypotheses Generation 65 5.4.4 Pose Clustering 67 5.4.5 Iterative Closest Point Refinement 68 Chapter 6 Dual-arm Object Locating 70 6.1 Dual-arm Motion for Locating Object 70 6.2 Object-locating Control Strategy 76 Chapter 7 Experimental Results and Analysis 79 7.1 Experimental Setup 79 7.1.1 Overview of the Procedures of the Simulations and Experiments 79 7.1.2 Hardware Platform 84 7.1.3 Software Platform 89 7.2 Calibration and Evaluation 90 7.2.1 Hand-eye Calibration 90 7.2.2 Base Frame Calibration 99 7.3 Pose Estimation for In-hand Workpiece 104 7.3.1 Simulation 106 7.3.2 Experiment 124 7.4 Robotic Workpiece-loading Application 140 7.4.1 Without Object-locating Control 144 7.4.2 With Object-locating Control 162 7.5 Summary 188 7.5.1 Discussion of Calibration 188 7.5.2 Pose Estimation for In-hand Workpiece 191 7.5.3 Robotic Workpiece-loading Application 194 Chapter 8 Conclusions and Future Works 197 8.1 Conclusions 197 8.2 Future Works 199 References 201 | |
| dc.language.iso | zh-TW | |
| dc.subject | 工件定位控制 | zh_TW |
| dc.subject | 點對特徵 | zh_TW |
| dc.subject | 製造自動化 | zh_TW |
| dc.subject | 工件上料 | zh_TW |
| dc.subject | 雙手臂機器人 | zh_TW |
| dc.subject | 最佳視角規劃 | zh_TW |
| dc.subject | 路徑規劃 | zh_TW |
| dc.subject | next-best view planning | en |
| dc.subject | object-locating control | en |
| dc.subject | motion planning | en |
| dc.subject | manufacturing automation | en |
| dc.subject | workpiece loading | en |
| dc.subject | dual-arm robotic system | en |
| dc.subject | point pair feature | en |
| dc.title | 基於標誌物多視角姿態估測之雙手臂協同物體定位系統用於工件上料自動化 | zh_TW |
| dc.title | Coordinated Object Locating of Dual-arm Robotic System Using Marker-based Multi-view Pose Estimation for Autonomous Workpiece Loading | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李後燦(Hsin-Tsai Liu),黃正民(Chih-Yang Tseng),許志明 | |
| dc.subject.keyword | 製造自動化,工件上料,雙手臂機器人,最佳視角規劃,點對特徵,路徑規劃,工件定位控制, | zh_TW |
| dc.subject.keyword | manufacturing automation,workpiece loading,dual-arm robotic system,next-best view planning,point pair feature,motion planning,object-locating control, | en |
| dc.relation.page | 210 | |
| dc.identifier.doi | 10.6342/NTU202104465 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-11-09 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-0411202116455800.pdf 授權僅限NTU校內IP使用（校園外請利用VPN校外連線服務） | 15.06 MB | Adobe PDF |
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