工業(yè)機器人定位精度補償技術的研究與實現(xiàn)
發(fā)布時間：2018-12-08 16:32
【摘要】：工業(yè)機器人定位精度分為絕對定位精度和重復定位精度。目前工業(yè)機器人絕對定位精度低,導致在離線編程過程中出現(xiàn)期望位置與實際位置偏差較大的問題,該問題亟待解決。本文在詳盡分析國內(nèi)外現(xiàn)有定位精度補償技術的基礎上,重點研究參數(shù)誤差辨識的精度問題及適合在工業(yè)現(xiàn)場快速補償?shù)姆椒?以六自由度工業(yè)機器人為研究對象,對所提的補償方法進行理論探討,并結(jié)合實驗進行驗證分析。該研究對促進制造業(yè)轉(zhuǎn)型升級具有重大意義。本文主要完成的工作及研究成果如下:針對幾何參數(shù)不精確而使得工業(yè)機器人定位精度低的情況,提出了基于IEKF的幾何參數(shù)標定方法。通過建立幾何參數(shù)誤差模型,利用矢量積法構(gòu)建參數(shù)雅克比矩陣,采用IEKF算法對量測方程的非線性函數(shù)多次進行泰勒展開以降低線性化誤差,并在辨識過程中動態(tài)修正觀測向量,最后使用辨識得到的幾何參數(shù)誤差對幾何參數(shù)名義值進行修正。實驗結(jié)果表明,采用IEKF算法將定位平均誤差和標準差分別改善到83.30%和82.61%,且對于幾何參數(shù)誤差辨識的精度明顯高于標準EKF和LM-LS算法辨識的結(jié)果,驗證了所提方法的準確性。針對傳統(tǒng)測量設備昂貴、操作復雜及不適合在工業(yè)現(xiàn)場快速標定等問題,對傳統(tǒng)PSD標定方法展開研究,提出了基于PMPSD的幾何參數(shù)標定方法。通過建立空間多點虛擬約束模型,利用所提的位姿修正原理對激光發(fā)射器位姿及機器人關節(jié)轉(zhuǎn)角進行修正,使用LM算法對構(gòu)建的模型約束目標函數(shù)進行優(yōu)化處理,進而得到幾何參數(shù)誤差,有效地提高了標定效率。實驗結(jié)果表明,采用PMPSD標定方法避免了PSD反饋控制,能夠快速實現(xiàn)幾何參數(shù)標定,得到的幾何參數(shù)誤差與IEKF算法辨識及傳統(tǒng)PSD標定方法得到的數(shù)據(jù)相關性分別為0.8877和0.9488,具有較高的相關性,并且將定位平均誤差和標準差分別改善到78.28%和76.38%,進一步驗證了所提方法的有效性,并且具有一定的工程實用性。本文從參數(shù)誤差辨識精度、標定效率兩方面對工業(yè)機器人的定位精度補償技術進行了研究與改進。綜合以上分析,采用基于IEKF的幾何參數(shù)標定方法擁有更好的補償效果,適合在對定位精度要求高的工業(yè)應用中實施,而基于PMPSD的幾何參數(shù)標定方法適合在對要求標定效率高、定位精度較高的環(huán)境中使用,所提的兩種補償方法提高了工業(yè)機器人的定位精度。
[Abstract]:The positioning accuracy of industrial robot is divided into absolute positioning accuracy and repetitive positioning accuracy. At present, the absolute positioning accuracy of industrial robot is low, which leads to the problem that the expected position deviates greatly from the actual position in the off-line programming process, and this problem needs to be solved urgently. Based on the detailed analysis of the existing positioning accuracy compensation techniques at home and abroad, this paper focuses on the accuracy of parameter error identification and the method suitable for fast compensation in industrial field. The six-DOF industrial robot is taken as the research object. The proposed compensation method is discussed theoretically and verified by experiments. This research is of great significance to promote the transformation and upgrading of manufacturing industry. The main work and research results of this paper are as follows: in view of the imprecision of geometric parameters which makes the positioning accuracy of industrial robot low, a calibration method of geometric parameters based on IEKF is proposed. By establishing geometric parameter error model and using vector product method to construct parameter Jacobian matrix, IEKF algorithm is used to expand the nonlinear function of measurement equation many times in order to reduce the linearization error. In the process of identification, the observation vector is dynamically corrected, and the nominal value of the geometric parameter is corrected by using the geometric parameter error obtained from the identification. The experimental results show that the average positioning error and standard deviation are improved to 83.30% and 82.61% respectively by using IEKF algorithm, and the accuracy of geometric parameter error identification is obviously higher than that of standard EKF and LM-LS algorithm. The accuracy of the proposed method is verified. Aiming at the problems of expensive, complex operation and unsuitable for rapid calibration in industrial field, the traditional PSD calibration method is studied, and the geometric parameter calibration method based on PMPSD is proposed. By establishing the spatial multi-point virtual constraint model, using the proposed principle of position and pose correction to modify the position and attitude of the laser emitter and the robot joint angle, the LM algorithm is used to optimize the constraint objective function of the model. Then the geometric parameter error is obtained and the calibration efficiency is improved effectively. The experimental results show that the PMPSD calibration method avoids PSD feedback control and can quickly realize geometric parameter calibration. The correlation between the geometric parameter error and the data obtained by IEKF algorithm identification and traditional PSD calibration is 0.8877 and 0.9488, respectively. The average positioning error and standard deviation are improved to 78.28% and 76.38% respectively, which further verify the effectiveness of the proposed method and have certain engineering practicability. In this paper, the positioning accuracy compensation technology of industrial robot is studied and improved in terms of parameter error identification accuracy and calibration efficiency. Based on the above analysis, the geometric parameter calibration method based on IEKF has better compensation effect and is suitable for industrial application with high precision, while the geometric parameter calibration method based on PMPSD is suitable for high calibration efficiency. In the environment with high positioning accuracy, the two compensation methods proposed improve the positioning accuracy of industrial robots.
【學位授予單位】：江南大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242.2
[Abstract]:The positioning accuracy of industrial robot is divided into absolute positioning accuracy and repetitive positioning accuracy. At present, the absolute positioning accuracy of industrial robot is low, which leads to the problem that the expected position deviates greatly from the actual position in the off-line programming process, and this problem needs to be solved urgently. Based on the detailed analysis of the existing positioning accuracy compensation techniques at home and abroad, this paper focuses on the accuracy of parameter error identification and the method suitable for fast compensation in industrial field. The six-DOF industrial robot is taken as the research object. The proposed compensation method is discussed theoretically and verified by experiments. This research is of great significance to promote the transformation and upgrading of manufacturing industry. The main work and research results of this paper are as follows: in view of the imprecision of geometric parameters which makes the positioning accuracy of industrial robot low, a calibration method of geometric parameters based on IEKF is proposed. By establishing geometric parameter error model and using vector product method to construct parameter Jacobian matrix, IEKF algorithm is used to expand the nonlinear function of measurement equation many times in order to reduce the linearization error. In the process of identification, the observation vector is dynamically corrected, and the nominal value of the geometric parameter is corrected by using the geometric parameter error obtained from the identification. The experimental results show that the average positioning error and standard deviation are improved to 83.30% and 82.61% respectively by using IEKF algorithm, and the accuracy of geometric parameter error identification is obviously higher than that of standard EKF and LM-LS algorithm. The accuracy of the proposed method is verified. Aiming at the problems of expensive, complex operation and unsuitable for rapid calibration in industrial field, the traditional PSD calibration method is studied, and the geometric parameter calibration method based on PMPSD is proposed. By establishing the spatial multi-point virtual constraint model, using the proposed principle of position and pose correction to modify the position and attitude of the laser emitter and the robot joint angle, the LM algorithm is used to optimize the constraint objective function of the model. Then the geometric parameter error is obtained and the calibration efficiency is improved effectively. The experimental results show that the PMPSD calibration method avoids PSD feedback control and can quickly realize geometric parameter calibration. The correlation between the geometric parameter error and the data obtained by IEKF algorithm identification and traditional PSD calibration is 0.8877 and 0.9488, respectively. The average positioning error and standard deviation are improved to 78.28% and 76.38% respectively, which further verify the effectiveness of the proposed method and have certain engineering practicability. In this paper, the positioning accuracy compensation technology of industrial robot is studied and improved in terms of parameter error identification accuracy and calibration efficiency. Based on the above analysis, the geometric parameter calibration method based on IEKF has better compensation effect and is suitable for industrial application with high precision, while the geometric parameter calibration method based on PMPSD is suitable for high calibration efficiency. In the environment with high positioning accuracy, the two compensation methods proposed improve the positioning accuracy of industrial robots.
【學位授予單位】：江南大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242.2
【參考文獻】
相關期刊論文 前10條
1 范明爭;韓先國;;基于標定及補償提高串聯(lián)機器人定位精度方法[J];北京航空航天大學學報;2017年01期
2 黎文娟;喬標;王海龍;;工業(yè)機器人市場競爭新格局[J];政策w，
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