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

作者：Yao, Sheng^*; Zhang, Xianmin^*; Zhu, Benliang; Li, Hai; Yu, Longhuan; Fatikow, Sergej

来源：IEEE Transactions on Instrumentation and Measurement, 2023, 72: 5001411.

DOI：10.1109/TIM.2023.3234038

• Target tracking
• Feature extraction
• Nanopositioning
• Robot sensing systems
• Measurement by laser beam
• Lenses
• Sensor systems
• Feature matching
• marker-free tracking
• microvision-based sensing
• motion measurement
• nanopositioner
• phase correlation
• robotic micromanipulation
• velocity estimation

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 $\mu $ rad.

• 单位
  南方医科大学