Design and Test of a Robustness Evaluation System for Micro-Vision Motion Tracking Algorithms

Industrial applications of micro-vision motion tracking algorithms become increasingly prevalent. Unfortunately, out-of-focused-plane (OFP) displacements negatively impact in-focused-plane (IFP) motion-tracking accuracy of the micro-vision. This paper proposes a robustness evaluation system for micro-vision algorithms. The relationship between IFP accuracy degradation and OFP disturbances is quantified. First, a commercial spatial nanopositioning stage (com-SNPS) and an SNPS designed in the laboratory (lab-SNPS) were employed to build a robustness evaluation system. Two SNPSs were utilized to generate both IFP trajectories and specific OFP disturbances. Capacitive sensors were used to evaluate the IFP accuracy of different motion-tracking algorithms. Second, typical micro-vision motion tracking algorithms were selected. The combination of the static focusing method, template matching method, and region of interest retrieval method acted as test examples. Third, the proposed robustness evaluation system was tested. The focused plane was determined before the tests as a benchmark for calculating OFP displacements. The IFP accuracy degradation of chosen algorithms under specific OFP excitation was measured. Test results demonstrate different IFP degradation characteristics of the chosen algorithm at the origin or during the standard motion trajectory. This paper contributes to developing a robust micro-vision motion tracking algorithm.