Abstract

Industrial robots are defined as robot systems for manufacturing, with feature programmability, certain automation, and capability to move on several axes. However, the insufficient accuracy has limited the industrial robots to many potential applications in aerospace manufacturing. Typical accuracy requirement in aerospace manufacturing, such as drilling and fastening, are $\pm0.20mm$ or less. Unfortunately, the discrepancy between a virtual-model robot and the corresponding real robot can even reach around $8\sim15mm$ due to the deflection of the mechanical structure and tolerances. Therefore, accuracy enhancement is highly significant in order to expand industrial robots to more applications in aerospace manufacturing. Visual servoing is extensively applied to control industrial robots with the help of the visual information feedback, especially for unmodeled environment. In recent decades, using visual servoing to reach the desired pose precisely has attracted the attention of many researchers. In this thesis research, three visual servoing-based control schemes are proposed to target at the accuracy enhancement of positioning and path tracking.

The research work in this thesis includes four parts. First, an adaptive Kalman filter (AKF) is developed to estimate the pose information of the objects in Cartesian space from the measurements of the visual sensor with noises. In order to address the difficulty in obtaining precise process error covariance and measurement error covariance, an adaptive algorithm is proposed to tune the covariance matrices so that the Kalman filter can produce synchronous pose estimations even when the objects are moving at certain acceleration or high speed. In this research, a photogrammetry sensor, C-Track 780 is selected as the visual sensor. The original measurement data from C-Track 780 are contaminated with the noises. The proposed AKF algorithm is developed to process the measurement data from C-Track 780 to obtain smooth pose information for visual servoing.

Second, an effective dynamic pose correction (DPC) scheme for industrial robots is proposed to enhance the pose reaching accuracy for satisfying both position and orientation precision requirement. By applying the DPC scheme, the end-effector of an industrial robot can approach the poses in its reachable workspace with high accuracy. Some experiments are implemented on an industrial robot, FANUC M20-iA, by using C-Track 780. The experimental results demonstrate high pose accuracy ($\pm0.050mm$ for position and $\pm0.050deg$ for orientation).

In the third part, a practical dynamic path tracking (DPT) scheme for industrial robots is elaborated for improving the path tracking accuracy. The proposed DPT scheme is designed to realize 3D dynamic path tracking by correcting the robot movement in real time. By using the proposed DPT scheme, the industrial robot can be controlled to follow the pre-planned path with high tracking accuracy. The dynamic stability for the robot system with the proposed DPT scheme is proved theoretically through Lyapunov function. Moreover, the effectiveness of the proposed DPT scheme is verified by the experiments on FANUC M20-iA with C-Track 780. The experimental results show the high path tracking accuracy ($\pm0.20mm$ for position and $\pm0.10deg$ for orientation) is achieved.

In the last part, adaptive iterative learning control (AILC) in parallel with the proposed DPT scheme is proposed to update the time-varying control parameters along iteration axis and calculate new compensation to adjust the control inputs produced by the DPT module at each time interval based on the memorized data information and current feedback. Three experiments in different situations (without path correction, with DPT control, and with AILC control) are carried out for the comparison. The pose accuracy can be stably confined to less than $0.10mm$ for position and $0.05deg$ for orientation. Moreover, the repetitive disturbances can be also overcome within certain iterations so that the vibrations can be significantly reduced. Therefore, the AILC algorithm proposed verified to be effective to further improve the DPT scheme.

The research work in this thesis explores various schemes to enhance the positioning and path tracking accuracies for 6-DOF industrial robots. The proposed schemes, DPC, DPT and AILC, are proved to be effective on some FANUC robots which can be representative in 6-DOF articulated industrial robots for manufacturing.