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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 機械工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87950
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor李宇修zh_TW
dc.contributor.advisorYu-Hsiu Leeen
dc.contributor.author陸彥宏zh_TW
dc.contributor.authorYan-Hong Luen
dc.date.accessioned2023-07-31T16:29:50Z-
dc.date.available2023-11-09-
dc.date.copyright2023-07-31-
dc.date.issued2023-
dc.date.submitted2023-06-30-
dc.identifier.citation[1]INKULU, Anil Kumar; BAHUBALENDRUNI, MVA Raju; DARA, Ashok. Challenges and opportunities in human robot collaboration context of Industry 4.0-a state of the art review. Industrial Robot: the international journal of robotics research and application, 2022, 49.2: 226-239.
[2]BROGÅRDH, Torgny. Present and future robot control development—An industrial perspective. Annual Reviews in Control, 2007, 31.1: 69-79.
[3]LISKA, Jindrich; VANICEK, Ondrej; CHALUS, Michal. Hand-eye calibration of a laser profile scanner in robotic welding. In: 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2018. p. 316-321.
[4]LISKA, Jindrich; CHALUS, Michal; VANICEK, Ondrej. Iterative refinement of hand-eye calibration. In: 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE). IEEE, 2018. p. 457-462.
[5]ZHU, Zhenqi, et al. Calibration of laser displacement sensor used by industrial robots. Optical Engineering, 2004, 43.1: 12-13.
[6]LI, Jianfeng, et al. Large depth-of-view portable three-dimensional laser scanner and its segmental calibration for robot vision. Optics and Lasers in Engineering, 2007, 45.11: 1077-1087.
[7]WAGNER, Maximilian, et al. Self-calibration method for a robotic based 3D scanning system. In: 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 2015. p. 1-6.
[8]CUI, Haihua, et al. A novel flexible two-step method for eye-to-hand calibration for robot assembly system. Measurement and Control, 2020, 53.9-10: 2020-2029.
[9]WANG, Gang, et al. Simultaneous calibration of multicoordinates for a dual-robot system by solving the AXB= YCZ problem. IEEE Transactions on Robotics, 2021, 37.4: 1172-1185.
[10]YIN, Shibin, et al. A vision-based self-calibration method for robotic visual inspection systems. Sensors, 2013, 13.12: 16565-16582.
[11]DE SOUSA, Gil Boyé, et al. 3D metrology using a collaborative robot with a laser triangulation sensor. Procedia Manufacturing, 2017, 11: 132-140.
[12]LEMBONO, Teguh Santoso; SUÁREZ-RUIZ, Francisco; PHAM, Quang-Cuong. SCALAR: Simultaneous calibration of 2-D laser and robot kinematic parameters using planarity and distance constraints. IEEE transactions on automation science and engineering, 2019, 16.4: 1971-1979.
[13]MURALI, Prajval Kumar, et al. In situ translational hand-eye calibration of laser profile sensors using arbitrary objects. In: 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. p. 11067-11073.
[14]LIU, Sujie, et al. Automatic Calibration Algorithm of Robot TCP Based on Binocular Vision. In: Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System. 2021. p. 244-249.
[15]SORKINE-HORNUNG, Olga; RABINOVICH, Michael. Least-squares rigid motion using svd. Computing, 2017, 1.1: 1-5.
[16]SARABANDI, Soheil; THOMAS, Federico. A survey on the computation of quaternions from rotation matrices. Journal of mechanisms and robotics, 2019, 11.2.
[17]AL-SHARADQAH, Ali; CHERNOV, Nikolai. Error analysis for circle fitting algorithms. 2009.
[18]HELWIG, Nathaniel E. Parameter Estimation. 2020.
[19]LIN, Po Ting, et al. Parametrically Modeled DH Table for Soft Robot Kinematics: Case Study for A Soft Gripper. In: Advances in Mechanism and Machine Science: Proceedings of the 15th IFToMM World Congress on Mechanism and Machine Science 15. Springer International Publishing, 2019. p. 617-625.
[20]SOONG, Tsu T. Fundamentals of probability and statistics for engineers. John Wiley & Sons, 2004.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87950-
dc.description.abstract定位設備是機器人工具中心點在空間中註冊與環境和工件相對位置的重要設備,當機器手臂為了因應不同工作而裝載不同工具時,能夠計算出工具施作點的新位置進行新任務。然而商用的校正設備除了價格不菲、設置昂貴,更換場域使用時也受制於廠商的技術服務項目。有鑑於此,本論文開發了一個以簡易遮斷式十字雷射感測器為基礎、用以校正定位設備的演算法。該十字雷射有四個自由度,通過一系列指定的機器人與雷射感測器運動、以及感測器觀察到的開關信號,可以估測出雷射感測器坐標系相對於已知機器人坐標系的相對旋轉和平移、並且作為伴隨產物計算出工具中心點相對手臂端點的位移。該演算法先在虛擬環境中對一工業用六軸串聯式機器人進行模擬測試,之後在硬體上進行實驗驗證,能夠達到 0.07 mm的精度。zh_TW
dc.description.abstractThe positioning device is an important equipment in the robotic tool center point that registers the relative position of the environment and workpieces in space, when the robotic arm is required to accommodate different tasks by mounting different tools, it is capable of calculating the new position of the tool's working point for performing a new task, however, commercial calibration equipment is not only expensive in terms of price and requires costly setup, but also its usage in different settings is limited by the technical service offerings provided by the manufacturers. In view of this, this thesis presents an algorithm based on a simple interruption cross-laser sensor to calibrate positioning equipment, the cross-laser sensor has four degrees of freedom, through a sequence of predetermined movements of the robot and laser sensor as well as the switch signals observed by the sensor, it enables the estimation of the relative rotation and translation between the coordinate system of the laser sensor and the known robot coordinate system, furthermore, it calculates the displacement of the tool center point relative to the end-effect of the robotic arm as an accompanying result. The algorithm is initially tested through simulation on an industrial six-axis serial robot in a virtual environment and subsequently validated through experimental tests on the hardware, it achieves an accuracy of 0.07 mm.en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-07-31T16:29:49Z
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dc.description.provenanceMade available in DSpace on 2023-07-31T16:29:50Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontents口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
目錄 iv
圖片列表 vii
表格清單 x
Chapter 1 介紹 1
1.1 研究背景 2
1.2 文獻回顧 3
Chapter 2 問題描述 11
2.1 機械手臂與感測器的坐標轉換和未知的工具中心前端 13
2.2 機械手臂架構 16
2.3 十字雷射感測器架構 18
Chapter 3 方法 21
3.1 計算工具端點中心 22
3.2 手臂與感測器原點間齊次轉換矩陣之校正演算法 25
3.3 掃描工具前端 27
3.3.1 步驟一 28
3.3.2 步驟二 28
3.4 十字雷射坐標系的三個尤拉角 30
3.4.1 步驟三 31
3.4.2 步驟四 35
3.5 工具長度的向量: 37
3.5.1 步驟五 37
3.5.2 步驟六 41
3.6 迭代的改善 42
Chapter 4 演算法模擬驗證 47
4.1 雷射遮斷訊號的模擬 47
4.1.1 移動訊號的模擬 48
4.1.2 旋轉訊號的模擬 50
4.2 比較工具真實與模擬的數值 52
4.3 迭代的模擬 54
4.4 蒙特卡洛模擬與誤差範圍 55
Chapter 5 實驗環境 59
5.1 硬體設置 61
5.1.1 機械手臂的操作 62
5.1.2 感測器的操作 63
5.2 使用的工具 65
5.2.1 計算相對高度的3D列印工具 65
5.2.2 演算法誤差評估工具 66
5.2.3 球接頭工具 66
5.3 計算工具向量流程 67
5.4 誤差分析 68
Chapter 6 總結 75
REFERENCE 76
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dc.language.isozh_TW-
dc.subject工具中心點zh_TW
dc.subject十字雷射感測器zh_TW
dc.subject定位設備zh_TW
dc.subjecttool center pointen
dc.subjectequipment calibrationen
dc.subjectcross-laser sensoren
dc.title使用雷射遮斷感測器之機械手臂設備定位校正技術zh_TW
dc.titleEquipment Calibration with a Laser Interruption Sensoren
dc.typeThesis-
dc.date.schoolyear111-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee陳政維;王富正;葉奕良zh_TW
dc.contributor.oralexamcommitteeCheng-Wei Chen;Fu-Cheng Wang;Yi-Liang Yeen
dc.subject.keyword定位設備,十字雷射感測器,工具中心點,zh_TW
dc.subject.keywordequipment calibration,cross-laser sensor,tool center point,en
dc.relation.page78-
dc.identifier.doi10.6342/NTU202301081-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2023-06-30-
dc.contributor.author-college工學院-
dc.contributor.author-dept機械工程學系-
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