A robotic framework for high-throughput and multi-view 3D digital image correlation (3D-DIC): Increasing measurement volume and versatility for deformation analysis

Three-dimensional digital image correlation (3D-DIC) is a widely applicable, non-contact optical imaging technique for accurately quantifying full-field surface displacements and strains in materials and structures. However, conventional 3D-DIC implementations relying on fixed stereo camera positions face trade-offs between the field-of-view and spatial resolution and lack high-throughput for long-duration measurements. Here we present an integrated robotic 3D-DIC framework that employs an industrial robotic arm to autonomously and repeatedly reposition stereo cameras. This enables automated calibration, monitoring of multiple samples over extended periods, and expansion of the effective spatial coverage and data throughput, all while maintaining calibration stability and measurement fidelity. We validate this approach on rigid and deforming reference samples and demonstrate its ability to quantify material deformation of bio-composite samples simultaneously during the drying process. Under robotic repositioning, rigid samples exhibit stable displacement and strain measurements while benefiting from significantly increased volumetric coverage and reduced manual oversight. Thus, the proposed system improves experimental efficiency and allows for the incorporation of advanced techniques, such as multi-view stitching, to characterize complex geometries with higher effective resolution. When applied to slowly deforming bio-composites, the system can capture time-lapse images from multiple viewpoints, providing a more comprehensive assessment of complex, evolving material behaviors. These enhancements in 3D-DIC further improve geometric accuracy, increase data density, and expand applicability to a broader range of materials and experimental conditions. Ultimately, the proposed robot-assisted 3D-DIC system creates a robust, high-throughput monitoring framework for bio-fabrication, additive manufacturing, and advanced composite processing, paving the way for targeted programming of shape changes, among other applications. • The first integration of a robot-controlled stereo camera 3D-DIC system. • Validation analyses revealed high DIC accuracies for long-term measurements. • The versatility of the robot allows simultaneous analysis of multiple samples (Throughput). • Subdividing large objects and stitching 3D-DIC analyses improves spatial resolution. • The system facilitates multi-view and multi-angle analysis of complex-shaped objects (Coverage).

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Publication Details

Journal
Robotics and Computer-Integrated Manufacturing
Published
2025-11-26
DOI
https://doi.org/10.1016/j.rcim.2025.103187
Citations
1
Primary Topic
Optical measurement and interference techniques
Type
article
Field-Weighted Citation Impact
1.28

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article

A robotic framework for high-throughput and multi-view 3D digital image correlation (3D-DIC): Increasing measurement volume and versatility for deformation analysis

Kaiyang Yin, Özgüç Bertuğ Çapunaman, Benay Gürsoy, Max D. Mylo et al.
1 citations
Robotics and Computer-Integrated Manufacturing
Optical measurement and interference techniques
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article

A robotic framework for high-throughput and multi-view 3D digital image correlation (3D-DIC): Increasing measurement volume and versatility for deformation analysis

Kaiyang Yin, Özgüç Bertuğ Çapunaman, Benay Gürsoy, Max D. Mylo, Alale Mohseni, Dennis Dombrovskij
article en
1 citations

Abstract

Three-dimensional digital image correlation (3D-DIC) is a widely applicable, non-contact optical imaging technique for accurately quantifying full-field surface displacements and strains in materials and structures. However, conventional 3D-DIC implementations relying on fixed stereo camera positions face trade-offs between the field-of-view and spatial resolution and lack high-throughput for long-duration measurements. Here we present an integrated robotic 3D-DIC framework that employs an industrial robotic arm to autonomously and repeatedly reposition stereo cameras. This enables automated calibration, monitoring of multiple samples over extended periods, and expansion of the effective spatial coverage and data throughput, all while maintaining calibration stability and measurement fidelity. We validate this approach on rigid and deforming reference samples and demonstrate its ability to quantify material deformation of bio-composite samples simultaneously during the drying process. Under robotic repositioning, rigid samples exhibit stable displacement and strain measurements while benefiting from significantly increased volumetric coverage and reduced manual oversight. Thus, the proposed system improves experimental efficiency and allows for the incorporation of advanced techniques, such as multi-view stitching, to characterize complex geometries with higher effective resolution. When applied to slowly deforming bio-composites, the system can capture time-lapse images from multiple viewpoints, providing a more comprehensive assessment of complex, evolving material behaviors. These enhancements in 3D-DIC further improve geometric accuracy, increase data density, and expand applicability to a broader range of materials and experimental conditions. Ultimately, the proposed robot-assisted 3D-DIC system creates a robust, high-throughput monitoring framework for bio-fabrication, additive manufacturing, and advanced composite processing, paving the way for targeted programming of shape changes, among other applications. • The first integration of a robot-controlled stereo camera 3D-DIC system. • Validation analyses revealed high DIC accuracies for long-term measurements. • The versatility of the robot allows simultaneous analysis of multiple samples (Throughput). • Subdividing large objects and stitching 3D-DIC analyses improves spatial resolution. • The system facilitates multi-view and multi-angle analysis of complex-shaped objects (Coverage).

Robotics and Computer-Integrated ManufacturingVol. 99
Pennsylvania State University (US), University of Freiburg (DE), University of Southern Denmark (DK), Chinese Academy of Sciences (CN), Ningbo Institute of Industrial Technology (CN)
University of Pennsylvania, Pennsylvania State University
Openalex Percentile: Top 14%
Optical measurement and interference techniques
1.28
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