Kinematics, pattern recognition, and motion control of mask–panel alignment system

Abstract Kinematics, pattern recognition, and motion control methods are investigated as an integrated approach for a mask–panel visual alignment system, which consists of the vision system to extract the mask–panel misalignment and the stage control system to compensate for it. First, a 4PPR alignment mechanism is considered and the inverse kinematic solution is found out to define the relationship between the mask–panel misalignment and the displacements of active joints. Then, a fast alignment mark recognition algorithm is proposed in terms of the geometric template matching (GTM), which is specific to simply shaped patterns but computationally much efficient compared with general correlation-based matchings. Finally, the kinematic solution and the developed vision algorithm are incorporated to implement a two-stage position-based visual servo, where both original fine images and reduced coarse ones are utilized together and the GTM plays a crucial role in achieving a near real-time visual feedback. Experimental results are shown to demonstrate the effectiveness of the GTM-based two-stage alignment control.