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◆ Micromachines2026-08-29

Two-Dimensional, Vision-Based Measurement for Experimental Characterization of Planar Compliant Mechanisms: A Critical Review and Uncertainty-Aware Framework.

Rohan R Ozarkar, Nilesh P Salunke, Prajitsen G Damle, Shakeelur Raheman, Khursheed B Ansari

原始摘要(英文原文)· Original abstract
In planar compliant mechanisms, single-input dual-output (SIDO) displacement amplifiers driven by piezoelectric actuators are frequently used in precision positioning, micro/nano manipulation, and biomedical microdevices. Accurate experimental verification of these mechanisms remains challenging because traditional contact sensors can add excess stiffness and impact the structure's normal behavior, and single-axis interferometers cannot measure multiple points simultaneously. In contrast, 2D vision-based measurement offers a non-contact alternative capable of capturing full planar motion and synchronized displacement tracking within a single image frame. This paper reviews the literature on camera calibration, homography-based planar reconstruction, sub-pixel edge extraction, vision-based characterization of compliant mechanisms, and benchmarking of vision systems against laser interferometers and coordinate measuring machines (CMMs). In the review, the SIDO-CDAM developed by Ozarkar et al. based on the Instantaneous Center Building Block (IC-BB) approach has been chosen as the target characterization system. The reviewed studies confirm that the major technical components needed for a high-precision 2D vision framework have been independently validated. However, there seems to be a lack of an integrated framework designed for synchronized dual-output SIDO-CDAM characterization. To overcome this gap, a seven-layer 2D vision-based characterization framework is proposed for scalable inspection of prototype-scale and MEMS-scale compliant mechanisms.
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Two-Dimensional, Vision-Based Measurement for Experimental Characterization of Planar Compliant Mechanisms: A Critical Review and Uncertainty-Aware Framework. — 科研速览 Science Skim