基于在線位姿測(cè)控系統(tǒng)的工業(yè)機(jī)器人定位精度優(yōu)化
[Abstract]:Industrial robot is regarded as the main component of intelligent manufacturing system in modern manufacturing technology. With the development of "Industry 4.0" High-end Manufacturing Technology Plan and "made in China 2025" National Strategic Plan in Germany, the importance of digital flexible machining system based on industrial robot is rising rapidly in the field of industry. However, the absolute positioning accuracy of industrial robots is not enough to meet the needs of precision machining. At present, although the robot positioning accuracy can be improved to some extent by modifying the kinematics parameter error of the robot, the kinematics model of the robot can not describe the actual position and pose of the robot completely and accurately. And off-line calibration can not reflect the robot environment, load and other interference. Therefore, this paper studies a real-time measurement and control system based on external measurement and control system to measure the position of robot terminal and optimize the compensation of robot positioning accuracy. Through the on-line measurement and compensation of the external measurement and control system, the real-time position and pose information of the robot terminal can be obtained, which not only simplifies the complex modeling process of the robot, adapts to the change of the actual situation, but also can reflect the comprehensive error of the robot. In this paper, a six-degree-of-freedom position and pose on-line measurement system is developed by using a close range photography system, a biaxial inclination measuring instrument and a PC machine. The six-degree-of-freedom pose information of the robot end-actuator is obtained in real-time by combining inertial measurement. In this paper, an off-line parameter calibration method for robot is developed by combining off-line error calibration technology with terminal measurement technology, off-line method and on-line method. The multi-sensor data fusion method based on Kalman filter and matrix weighted linear minimum variance optimal fusion criterion is studied. The advanced dynamic prediction and redundant data fusion of robot online pose measurement system are realized. At the same time, a method of measuring the three-dimensional attitude angle by combining the calculation value of the industrial robot encoder with the biaxial inertial dip meter is developed. In this paper, the optimum working range and working conditions of on-line pose measurement system are studied and analyzed. A coordinate system transformation method based on point cloud feature line coincidence is proposed, which can accurately and quickly unify the coordinate system between the online position and attitude measurement system and the industrial robot. Based on KUKA KR 5 arc industrial robot, a set of real-time measurement and control software algorithm is developed. In the laboratory environment, the real-time communication and feedback compensation between the on-line position and attitude measurement system and the industrial robot are realized.
【學(xué)位授予單位】:天津大學(xué)
【學(xué)位級(jí)別】:博士
【學(xué)位授予年份】:2016
【分類號(hào)】:TP242
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