Design and Test of a Spatial Nanopositioner for Evaluating the Out-of-Focus-Plane Performance of Micro-Vision

Abstract

Micro-vision possesses high in-focus-plane motion tracking accuracy. Unfortunately, out-of-focus-plane displacements cannot be avoided, decreasing the in-focus-plane tracking accuracy of micro-vision. In this paper, a spatial nanopositioner is proposed to evaluate the out-of-focus-plane performance of a micro-vision system. A piezoelectric-actuated spatial multi-degree-of-freedom (multi-DOF) nanopositioner is introduced. Three in-plane Revolute-Revolute-Revolute-Revolute (RRRR) compliant parallel branched chains produce in-focus-plane motions. Three out-of-plane RRRR chains generate out-of-focus-plane motions. A typical micro-vision motion tracking algorithm is presented. A general grayscale template matching (GTM) approach is combined with the region of interest (ROI) method. The in-focus-plane motion tracking accuracy of the micro-vision system is tested. Different out-of-focus-plane displacements are generated using the proposed nanopositioner. The accuracy degradation of the in-focus-plane motion tracking is evaluated. The experimental results verify the evaluation ability of the proposed nanopositioner.

Reinforcement Learning-Based Adaptive Control of a Piezo-Driven Nanopositioning System

“…where k u ∈ R 2×2 is the control gain matrix and (20) where σ(t) = σ 1 e −σ2 with σ 1 > 0 and σ 2 > 0. The adaptive law of ω(t) is given by…”