工业机器人定位精度补偿技术的研究与实现
发布时间：2018-12-08 16:32
【摘要】：工业机器人定位精度分为绝对定位精度和重复定位精度。目前工业机器人绝对定位精度低,导致在离线编程过程中出现期望位置与实际位置偏差较大的问题,该问题亟待解决。本文在详尽分析国内外现有定位精度补偿技术的基础上,重点研究参数误差辨识的精度问题及适合在工业现场快速补偿的方法,以六自由度工业机器人为研究对象,对所提的补偿方法进行理论探讨,并结合实验进行验证分析。该研究对促进制造业转型升级具有重大意义。本文主要完成的工作及研究成果如下:针对几何参数不精确而使得工业机器人定位精度低的情况,提出了基于IEKF的几何参数标定方法。通过建立几何参数误差模型,利用矢量积法构建参数雅克比矩阵,采用IEKF算法对量测方程的非线性函数多次进行泰勒展开以降低线性化误差,并在辨识过程中动态修正观测向量,最后使用辨识得到的几何参数误差对几何参数名义值进行修正。实验结果表明,采用IEKF算法将定位平均误差和标准差分别改善到83.30%和82.61%,且对于几何参数误差辨识的精度明显高于标准EKF和LM-LS算法辨识的结果,验证了所提方法的准确性。针对传统测量设备昂贵、操作复杂及不适合在工业现场快速标定等问题,对传统PSD标定方法展开研究,提出了基于PMPSD的几何参数标定方法。通过建立空间多点虚拟约束模型,利用所提的位姿修正原理对激光发射器位姿及机器人关节转角进行修正,使用LM算法对构建的模型约束目标函数进行优化处理,进而得到几何参数误差,有效地提高了标定效率。实验结果表明,采用PMPSD标定方法避免了PSD反馈控制,能够快速实现几何参数标定,得到的几何参数误差与IEKF算法辨识及传统PSD标定方法得到的数据相关性分别为0.8877和0.9488,具有较高的相关性,并且将定位平均误差和标准差分别改善到78.28%和76.38%,进一步验证了所提方法的有效性,并且具有一定的工程实用性。本文从参数误差辨识精度、标定效率两方面对工业机器人的定位精度补偿技术进行了研究与改进。综合以上分析,采用基于IEKF的几何参数标定方法拥有更好的补偿效果,适合在对定位精度要求高的工业应用中实施,而基于PMPSD的几何参数标定方法适合在对要求标定效率高、定位精度较高的环境中使用,所提的两种补偿方法提高了工业机器人的定位精度。
[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.
【学位授予单位】：江南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：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.
【学位授予单位】：江南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242.2
【参考文献】
相关期刊论文 前10条
1 范明争;韩先国;;基于标定及补偿提高串联机器人定位精度方法[J];北京航空航天大学学报;2017年01期
2 黎文娟;乔标;王海龙;;工业机器人市场竞争新格局[J];政策w，
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