A Microvision-Based Motion Measurement System for Nanopositioners Using the Feature-to-Phase Method

摘要

The development of automation at the nanoscale has been calling for precision motion sensing for robotic nanopositioners. This study presents a microvision-based measurement system for the accurate and efficient motion sensing of three-degree-of-freedom (DOF) nanopositioners. In this measurement system, an optimized target searching (OTS) scheme is proposed for automatic tracking target selection. A strategy is designed to combine feature matching with phase correlation to balance the measurement accuracy and efficiency. By proposing a multiple target tracking scheme, high-precision angular measurement is achieved, and velocity estimation is also provided in this microvision-based measurement system. Subsequently, offline simulations and online experiments are performed to comprehensively evaluate the performances of the microvision-based system with comparisons to traditional instrumentation. The simulation and experimental results demonstrate that the proposed system and marker-free method can realize excellent extensibility, strong robustness, and high precision of motion tracking for the nanopositioners, with measurement accuracy higher than 93 nm and 96 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> rad.