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Design and test of a robustness evaluation system for micro-vision tracking algorithms.

Ruizhou Wang¹, Yulong Zhang¹, Hua Wang²

¹State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China.

The Review of Scientific Instruments

|February 3, 2025

Summary

This study introduces a new system to evaluate micro-vision tracking algorithms under out-of-focused-plane (OFP) disturbances. It quantifies how OFP issues affect in-focused-plane (IFP) accuracy, aiding the development of more robust tracking solutions.

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Area of Science:

* Optics and Vision Science
* Precision Engineering
* Algorithm Development

Background:

* Micro-vision tracking is vital for industrial applications.
* Out-of-focused-plane (OFP) disturbances degrade in-focused-plane (IFP) tracking accuracy.
* Existing methods lack robust evaluation under OFP conditions.

Purpose of the Study:

* To propose and validate a robustness evaluation system for micro-vision tracking algorithms.
* To quantify the relationship between OFP disturbances and IFP accuracy.
* To contribute to the development of robust micro-vision tracking algorithms.

Main Methods:

* Developed a robustness evaluation system using commercial and lab-designed spatial nanopositioning stages (SNPS).
* Employed capacitive sensors to measure IFP accuracy.
* Tested traditional (constant-template, constant-ROI, constant-focusing) and robust (variable-template, variable-ROI, variable-focusing) algorithms.
* Defined the focused plane as the benchmark for OFP disturbance calculation.

Main Results:

* Demonstrated that OFP disturbances have varying impacts on IFP accuracy for different micro-vision algorithms.
* Quantified IFP accuracy degradation and improvement under specific OFP excitations.
* Validated the effectiveness of the proposed robustness evaluation system.

Conclusions:

* The developed system effectively evaluates micro-vision tracking algorithm robustness against OFP disturbances.
* Understanding OFP effects is crucial for designing accurate and reliable micro-vision systems.
* This work provides a foundation for creating more resilient industrial tracking solutions.