本文選題：工業(yè)機器人 + 運動學(xué)誤差�。� 參考：《華南理工大學(xué)》2016年博士論文

【摘要】：現(xiàn)代工業(yè)技術(shù)的進步促進了機器人性能的不斷提高,對工業(yè)機器人精度要求也不斷提高。特別是離線編程機器人廣泛應(yīng)用,使定位精度問題日益突出。為了提高機器人定位精度,即減小機器人的實際位姿和名義位姿間的誤差,利用統(tǒng)計分析方法改進了運動學(xué)誤差和非幾何誤差辨識方法,并根據(jù)機器人誤差源的分類提出了工業(yè)機器人誤差補償策略。本文研究了描述機器人末端位姿誤差的完整的運動學(xué)誤差參數(shù)選擇,并建立運動學(xué)誤差參數(shù)模型�；贖ayati方法修改Khalil的D-H齊次坐標矩陣,建立了各關(guān)節(jié)的運動學(xué)誤差參數(shù)模型,基于Stone模型建立了基礎(chǔ)坐標系和工具坐標系的誤差模型。研究了機器人位置誤差測量方法、測量坐標系和機器人坐標系的坐標轉(zhuǎn)換方法,提出通過3個位置點測量機器人姿態(tài)誤差的方法。基于機器人的正運動學(xué)和逆運動學(xué)方程,提出運動學(xué)誤差采用正運動學(xué)補償方法,非幾何誤差采用逆運動學(xué)誤差補償方法的策略。研究了兩種辨識運動學(xué)誤差的方法,分別為軸線誤差辨識方法和運動學(xué)誤差參數(shù)模型的辨識方法。建立機器人各單關(guān)節(jié)誤差到末端誤差的映射,對機器人各關(guān)節(jié)單軸運動產(chǎn)生的末端誤差進行了統(tǒng)計分析,利用統(tǒng)計結(jié)果確定了軸線法辨識機器人實際的運動學(xué)參數(shù)建立坐標系的次序。研究多點擬合空間圓的軸線方向和圓心的方法,根據(jù)所獲得的各關(guān)節(jié)軸線特征,依次建立了機器人各關(guān)節(jié)實際的坐標系,并反向求解獲得Hayati修改的D-H模型實際參數(shù)的方法。提出了統(tǒng)一的位置和姿態(tài)誤差辨識運動學(xué)誤差參數(shù)的模型,根據(jù)位置誤差和位姿誤差辨識機器人的運動學(xué)誤差參數(shù);提出了距離誤差辨識運動學(xué)誤差參數(shù)的方法。研究了運動學(xué)誤差的擴展雅克比矩陣逐項分析線性相關(guān)列向量的方法,以及剔除冗余運動學(xué)誤差參數(shù)的方法,改進了從基坐標系到工具坐標系依次剔除冗余誤差參數(shù)的準則,提出依據(jù)末端誤差統(tǒng)計分析結(jié)果剔除精度高的冗余誤差參數(shù)的準則,分析得到位姿誤差可辨識的28個無冗余運動學(xué)誤差參數(shù),位置誤差可辨識的25個無冗余運動學(xué)誤差參數(shù)。采用矩陣奇異值分解的方法(SVD方法),改進了擴展雅克比矩陣辨識運動學(xué)誤差參數(shù)的計算方法。基于統(tǒng)計方法估算辨識運動學(xué)誤差需要測量的次數(shù),減少了測量實驗次數(shù),保證了擴展雅克比矩陣求解運動學(xué)誤差參數(shù)的計算有效性。根據(jù)運動學(xué)誤差的辨識結(jié)果,分別完成機器人的位姿誤差補償、位置誤差補償和距離誤差補償,實驗結(jié)果表明采用統(tǒng)計分析的方法改進剔除冗余運動學(xué)誤差參數(shù)的方法,可進一步提高機器人的定位精度。利用舍去的二階運動學(xué)誤差建立的非幾何誤差補償準則,分別計算舍去的二階運動學(xué)誤差和非幾何誤差產(chǎn)生的末端誤差并比較兩者大小,由此選擇需要補償?shù)姆菐缀握`差源。確定補償機器人連桿自重和機器人末端負載引起的柔性誤差,建立了機器人關(guān)節(jié)的柔性誤差到機器人末端誤差的映射,基于統(tǒng)計方法分析了各關(guān)節(jié)的柔性誤差對末端誤差的影響,確定了需要柔性誤差補償?shù)年P(guān)節(jié)。本文采用3個步驟補償機器人的柔性誤差,辨識了機器人的柔性系數(shù)矩陣,在未加負載的情況下補償了連桿的自重,補償了由于加載負載產(chǎn)生的柔性誤差引起的非幾何誤差,實驗結(jié)果表明對統(tǒng)計分析選擇的需柔性誤差補償?shù)年P(guān)節(jié)進行補償,可提高機器人精度和減小外加負載產(chǎn)生的末端誤差,并為機械結(jié)構(gòu)直接補償柔性誤差提供研究基礎(chǔ)。
[Abstract]:The progress of modern industrial technology has promoted the continuous improvement of robot performance and improved the precision requirements of industrial robots. In particular, off-line programming robots are widely used to make the problem of positioning precision increasingly prominent. In order to improve the positioning accuracy of robots, that is, to reduce the error between the real position and the nominal position of the robot, and to use the statistics. The analysis method improves the kinematic error and the non geometric error identification method, and puts forward the industrial robot error compensation strategy according to the classification of the robot error source. This paper studies the complete kinematic error parameter selection of the robot terminal position and attitude error and establishes the model of the kinematic error parameter. Based on the Hayati method, the Khal is modified. The D-H homogeneous coordinate matrix of IL is used to establish the kinematic error model of each joint. Based on the Stone model, the error model of the basic coordinate system and the tool coordinate system is established. The measurement method of the robot position error, the coordinate system and the coordinate conversion method of the robot coordinate system are studied, and the attitude of the robot is measured by 3 position points. Based on the positive kinematics and inverse kinematics equations of the robot, the kinematic error is proposed by the positive kinematics compensation method, and the non geometric error adopts the strategy of the inverse kinematics error compensation method. Two methods of identifying the kinematic error are studied, which are the identification of the axis error and the identification of the kinematic error parameter model respectively. Method. The mapping of each joint error to the end error of each joint of the robot is set up, the end error of the single axis motion of each joint of the robot is statistically analyzed. The order of the axis method to identify the actual kinematic parameters of the robot is determined by the statistical results. According to the characteristics of each joint axis obtained by the method, the actual coordinate system of each joint of the robot is established in turn, and the method of obtaining the actual parameters of the D-H model modified by Hayati is solved reverse. The model of the unified position and attitude error identification of the kinematic error parameters is put forward, and the kinematics of the robot is identified according to the position error and the position error. The method to identify the kinematic error parameters of the distance error is proposed. The method of analyzing the linear correlation column vector by the extended Jacobian matrix of kinematic error and the method of eliminating the redundant kinematic error parameters are studied, and the criterion of eliminating redundant error parameters from the basic coordinate system to the tool seat system is improved. According to the criterion of eliminating the redundant error parameters with high accuracy according to the statistical analysis results of the end error, 28 non redundant kinematic error parameters can be identified, and 25 non redundant kinematic error parameters can be identified by the position error. The extended Jacobian matrix identification is improved by the method of matrix singular value decomposition (SVD method). The calculation method of the kinematic error parameters. Based on the statistical method, the number of times that the kinematic error needs to be measured is estimated, the times of the measurement are reduced and the calculation validity of the extended Jacobian matrix is guaranteed. According to the identification result of the kinematic error, the position error compensation and the position error of the robot are completed. The result of difference compensation and distance error compensation shows that the method of statistical analysis is used to improve the method of eliminating redundant kinematic error parameters, and the positioning accuracy of the robot can be further improved. By using the non geometric error compensation criterion established by the two order kinematic error, the two order kinematic error and non geometric error of the rounding are calculated respectively. The end error generated by the difference is compared with the size of the two. Therefore, the non geometric error source which needs compensation is chosen. The flexible error caused by the self weight of the connecting rod and the load of the robot end is determined. The mapping of the flexible error of the robot joint to the robot end error is established, and the flexible error pairs of the joints are analyzed based on the statistical method. In this paper, the flexible error of the robot is compensated by 3 steps, and the flexibility coefficient of the robot is compensated. The flexible coefficient matrix of the robot is identified. The weight of the connecting rod is compensated without the load, and the non geometric error caused by the flexible error caused by the load load is compensated. The joint compensation of the flexible error compensation for statistical analysis selection can improve the robot precision and reduce the end error generated by the applied load, and provide the research foundation for the direct compensation of the flexible error for the mechanical structure.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP242

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本文編號：2004136