An Improved Template-Matching-Based Pose Tracking Method for Planar Nanopositioning Stages Using Enhanced Correlation Coefficient

In the development and application of planar nanopositioning stages (PNSs), there is an urgent need to measure pose quickly and accurately. An improved pose measurement method based on template matching that can track in-plane three degree-of-freedom (3-DOF) motion at small scale with high performance is presented in this paper. To achieve higher tracking accuracy and robustness, the problem of pose measurement is first transformed into an enhanced correlation coefficient (ECC) -based parametric image matching problem. Subsequently, an efficient 3-DOF tacking algorithm based on inverse compositional searching strategy is developed in which the update of Hessian matrix caused by the nonlinear warp is avoided to improve the tracking frame rate. A series of simulations and experiments are conducted to evaluate the performance of the proposed method. The results show that the use of ECC can effectively improve the tracking robustness and accuracy, especially for angular measurement, compared to the sum of square difference (SSD) criterion. Besides, the tracking frame rate can be improved by using the developed algorithm even though the correlation function is much more complicated. Finally, application of the proposed method on a nanorobotic system for automatic in-plane 3-DOF alignment is demonstrated.