English  |  正體中文  |  简体中文  |  Items with full text/Total items : 889/889 (100%)
Visitors : 14653021      Online Users : 13
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://ccur.lib.ccu.edu.tw/handle/A095B0000Q/232

    Title: 六軸機械手臂誤差精度補償;6-axis Robotic Error Compensation
    Authors: 何致慨;HO, CHIH-KAI
    Contributors: 機械工程系研究所
    Keywords: 機械手臂;誤差補償;影像輔助辨識;Robotic arm;Error compensation;Image processing
    Date: 2017
    Issue Date: 2019-07-17
    Publisher: 機械工程系研究所
    Abstract: 現今工業朝向自動化產業發展,六軸機械手臂扮演著相當重要的角色,不論是焊接、夾取工件、循邊塗料等等高危險或重複性工作,都可由機械手臂取代,而對於六軸機械手臂的精度要求也越來越高。雖然機械手臂能完成重複性工作,卻無法偵測外界因素影響,如再結合攝影機輔助影像辨識,可讓六軸機械手臂的應用範圍更加廣泛。本論文將針對六軸機械手臂提出一套補償方法,大部分是針對機械手臂的末端點進行補償,但是當換到另一個位置時,又需再補償一次。本論文針對六軸機械手臂的各關節軸進行分析,定義平移誤差與旋轉誤差項次,並藉由量測儀器協助,求解誤差項次,再經由實驗驗證補償效果,除了針對單一路徑進行補償外,亦針對各關節軸進行單軸誤差補償,實驗結果中,有明顯地補償效果,能大幅地降低誤差,提升定位精度。機械手臂如沒有感測器的協助,只能進行簡單或是重複性的工作,當有了攝影機的輔助,機械手臂的應用範圍就更加廣泛,因此本論文結合攝影機與機械手臂,透過攝影機辨識目標物,分類顏色與形狀,再經由機械手臂進行夾取的動作,因此需針對攝影機的內部參數、外部參數與畸變參數進行校正,再經由矩陣轉換,將座標系轉移至機械手臂,最後讓機械手臂能自主式完成夾取目標物並分類。
    Now the industry moves toward automation and the 6-axis robotic arm becomes very indispensable during automation. No matter welding, grip components, edge coating, high risk and repeatability work etc., all can be replaced by the 6-axis robotic arm. Therefore, the accuracy requirement of 6-axis robotic arm is getting higher and higher. Although the robotic arm could accomplish repetitive work, but it can’t detect the disturbance from the external factors. If it is combined with camera for assistance, then the 6-axis robotic arm application can become more extensive.This thesis proposes a compensation method for 6-axis robotic arm. Most of the compensation methods are focused on 6-axis robotic arm’s end-effector. If the robot changes to the other position, that the experiment parameters should be compensated again. Thus, this thesis analyzes the axes of 6-axis robotic arm which define the translation error and rotation error first. Then using the measurement instrument assists and solves the geometric error. Through the experiments, the compensation method not only can compensate for a single path but also can compensate for each axis. The experimental results demonstrates very good compensation effect which greatly reduces the end-effector error and improves the positioning accuracy.If the robotic arm runs without the assistance of the sensor, it can only carries out simple work or repetitive work. The robotic arm application is more extensive when the camera is added for help. This thesis used camera together with the 6-axis robotic arm to identify the object. Classification of color and shape by camera then be used in robotic arm to grip the object. Therefore, the internal, external and distortion parameters of the camera should be calibrated. After the calibration, the camera coordinate system is transferred to the 6-axis robotic arm by matrix conversion. Finally, the 6-axis robotic arm can classify and grip the objects autonomously.
    Appears in Collections:[機械工程學系] 學位論文

    Files in This Item:

    File Description SizeFormat

    All items in CCUR are protected by copyright, with all rights reserved.

    版權聲明 © 國立中正大學圖書館網頁內容著作權屬國立中正大學圖書館


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback