Advanced Robotic Multimodal Imaging with Real-Time Motion Compensation for Dynamic Structural Health Monitoring
Keywords:
learning, case study, Epistemic games, GameFlow, Game evaluation, digital transformation, Maritime compliance, Electronic Data Interchange, Cross-border collaboration, Human-centric design, Gas leaks and fires, Internet of Things and Global System for Mobile Communications, Robotics-driven Imaging; Motion Correction; Multimodal; Porosity Analysis; Materials testing, Computer-based metrology; Non-Destructive TestingAbstract
Modern composite materials promise superior performance and load-bearing capabilities, yet evaluating their structural integrity remains challenging. Current testing methods, such as visual, thermographic, ultrasonic, optical, electromagnetic, terahertz, shearography, X-ray, and neutron imaging, are hampered by long scan durations, limited field of view, suboptimal accuracy, and high costs, particularly when applied to large structures.
This paper addresses these issues by introducing a novel robotic multimodal imaging system that overcomes the limitations of traditional methods. This system dynamically captures both static and dynamic properties of materials using advanced motion compensation techniques. By integrating multiple radiographic modalities into a coordinated robotic platform, it provides rapid, high-resolution imaging of composite materials of large structures without the need for disassembly.
The system was validated through simulations of a four-robot radiograph setup, treated as two single-plane systems. The 3D position and orientation of a cube phantom were determined by generating computer-based digitally reconstructed radiographs from a computed tomography model and applying a 3D line intersection method based on known imaging geometries. Comparisons between marker-based and markerless kinematics tracking methods yielded differences of only 0.03 mm in translation and 0.06° in rotation.
These findings demonstrate that the proposed system significantly reduces scan times and enhances accuracy, offering a robust, scalable solution for dynamic inspection in diverse fields such as aerospace and medical device manufacturing.
References
N. Michailidis, F. Stergioudi, H. Omar, D. N. Tsipas (2010) An image-based reconstruction of the 3D geometry of an Al open-cell foam and FEM modeling of the material response. 42(2). https://doi.org/10.1016/j.mechmat.2009.10.006
S. Gholizadeh (2016) A review of non-destructive testing methods of composite materials. 1, 50–57. https://doi.org/10.1016/j.prostr.2016.02.008
B. Wang, S. Zhong, T.-L. Lee, K. S. Fancey, J. Mi (2020) Non-destructive testing and evaluation of composite materials/structures: A state-of-the-art review. 12(4), 168781402091376. https://doi.org/10.1177/1687814020913761
S. C. Garcea, I. Sinclair, S. M. Spearing, P. J. Withers (2017) Mapping fibre failure in situ in carbon fibre reinforced polymers by fast synchrotron X-ray computed tomography. 149, 81–89. https://doi.org/10.1016/j.compscitech.2017.06.006
S. Borkowski, K. Knop (2016) Challenges Faced in Modern Quality Inspection. 7(3), 11–22. https://doi.org/10.1515/mper-2016-0022
N. Michailidis, F. Stergioudi, G. Maliaris, A. Tsouknidas (2014) Influence of galvanization on the corrosion fatigue performance of high-strength steel. 259, 456–464. https://doi.org/10.1016/j.surfcoat.2014.10.049
S. C. Garcea, Y. Wang, P. J. Withers (2018) X-ray computed tomography of polymer composites. 156, 305–319. https://doi.org/10.1016/j.compscitech.2017.10.023
J. E. See, C. G. Drury, A. Speed, A. Williams, N. Khalandi (2017) The Role of Visual Inspection in the 21st Century. 61(1), 262–266. https://doi.org/10.1177/1541931213601548
X. Xu, et al. (2024) A systematic review of ultrasonic techniques for defects detection in construction and building materials. 226, 114181. https://doi.org/10.1016/j.measurement.2024.114181
S. K. Dwivedi, M. Vishwakarma, Prof. A. Soni (2018) Advances and Researches on Non Destructive Testing: A Review. 5(2), 3690–3698. https://doi.org/10.1016/j.matpr.2017.11.620
E. Marble, T. Boles (2022) A Review of the Structural Characteristics of Aerospace Composites. 41(7), 749–753. https://doi.org/10.15354/si.22.re102
H. Kim, Y. Lin, T.-L. B. Tseng (2018) A review on quality control in additive manufacturing. 24(3), 645–669. https://doi.org/10.1108/RPJ-03-2017-0048
Y. Fu, X. Yao (2022) A review on manufacturing defects and their detection of fiber reinforced resin matrix composites. 8, 100276. https://doi.org/10.1016/j.jcomc.2022.100276
N. Baka, et al. (2014) Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy. 47(1), 122–129. https://doi.org/10.1016/j.jbiomech.2013.09.022
M. Jolly, et al. (2015) Review of Non-destructive Testing (NDT) Techniques and their Applicability to Thick Walled Composites. 38, 129–136. https://doi.org/10.1016/j.procir.2015.07.043
(2017) Standard Practice for Radiographic Examination Using Computed Radiography (Photostimulable Luminescence Method).
C. Tuloup, W. Harizi, Z. Aboura, Y. Meyer, K. Khellil, R. Lachat (2019) On the use of in-situ piezoelectric sensors for the manufacturing and structural health monitoring of polymer-matrix composites: A literature review. 215, 127–149. https://doi.org/10.1016/j.compstruct.2019.02.046
P. F. Tavares, S. C. Leemann, M. Sjöström, Å. Andersson (2014) The MAX IV storage ring project. 21(5), 862–877. https://doi.org/10.1107/S1600577514011503
(2015) Standard practice for radiographic examination of flat panel composites and sandwich core materials used in aerospace applications.
Herman. J. Woltring, P. van Roy, M. Hebbelinck, M. Osteaux, L. Verbruggen (1990) 3-D knee joint kinematics by magnetic resonance imaging. 23(4), 384. https://doi.org/10.1016/0021-9290(90)90127-O
G. Papaioannou (2024) A motion correction method for the moving target in robotic radiographic 2D and 3D imaging and robotics-driven computed tomography and other imaging modalities: Patent #20130100820.
L. Lucchetti, A. Cappozzo, A. Cappello, U. Della Croce (1998) Skin movement artefact assessment and compensation in the estimation of knee-joint kinematics. 31(11), 977–984. https://doi.org/10.1016/S0021-9290(98)00083-9
L. Lemieux, R. Jagoe, D. R. Fish, N. D. Kitchen, D. G. T. Thomas (1994) A patient-to-computed-tomography image registration method based on digitally reconstructed radiographs. 21(11), 1749–1760. https://doi.org/10.1118/1.597276
J. Weese, G. P. Penney, P. Desmedt, T. M. Buzug, D. L. G. Hill, D. J. Hawkes (1997) Voxel-based 2-D/3-D registration of fluoroscopy images and CT scans for image-guided surgery. 1(4), 284–293. https://doi.org/10.1109/4233.681173
W. Burton, C. Myers, M. Stefanovic, K. Shelburne, P. Rullkoetter (2024) Scan-Free and Fully Automatic Tracking of Native Knee Anatomy from Dynamic Stereo-Radiography with Statistical Shape and Intensity Models. 52(6), 1591–1603. https://doi.org/10.1007/s10439-024-03473-5
B. Prentice, et al Global fleet and MRO market forecast (2024-2034). www.oliverwyman.com
G. Papaioannou, G. Nianios, C. Mitrogiannis, D. Fyhrie, S. Tashman, K. H. Yang (2008) Patient-specific knee joint finite element model validation with high-accuracy kinematics from biplane dynamic Roentgen stereogrammetric analysis. 41(12), 2633–2638. https://doi.org/10.1016/j.jbiomech.2008.06.027
G. Papaioannou, M. Bottum, G. Fiedler (2007) Menisci displacement under joint load. 40(2), S158.
G. Papaioannou, et al (2004) Finite Element Modeling of the osteochondral defects in the human knee: Influence of defect size on cartilage rim stress and load redistribution to adjacent cartilage. 541–549. https://doi.org/10.1142/9789812702593_0057
P. Beillas (2004) A new method to investigate in vivo knee behavior using a finite element model of the lower limb. 37(7), 1019–1030. https://doi.org/10.1016/S0021-9290(03)00435-4
G. Papaioannou, C. K. Demetropoulos, Y. H. King (2010) Predicting the effects of knee focal articular surface injury with a patient-specific finite element model. 17(1), 61–68. https://doi.org/10.1016/j.knee.2009.05.001
G. Papaioannou, et al. (2011) Dynamic Radiography Imaging as a Tool in the Design and Validation of a Novel Intelligent Amputee Socket. https://doi.org/10.1007/94-007-0011-6_5
G. Papaioannou, C. Mitrogiannis, G. Nianios, G. Fiedler (2010) Assessment of amputee socket–stump–residual bone kinematics during strenuous activities using Dynamic Roentgen Stereogrammetric Analysis. 43(5), 871–878. https://doi.org/10.1016/j.jbiomech.2009.11.013
G. Papaioannou (2023) Automated radiographic imaging system and method for multimodal imaging protocols with motion correction system.
J. Neider, T. Davis, M. Woo (1998) OpenGL Programming Guide.
G. Papaioannou (2024) A Robotics-driven Multimodal Imaging System for Quality Inspection.
G. Papaioannou (2016) Robotic multi-mode radiological scanning system and method.
(2022) KINEMAGINE Helios Robotic Imaging system, Brochure and KINEDOSE Operating manual.
X. Lu, et al. (2024) High-Performance Flat-Panel Perovskite X-ray Detectors Enabled by Defect Passivation in Ruddlesden–Popper Perovskites. 16(11), 14006–14014. https://doi.org/10.1021/acsami.4c00232
J. Fuller, L.-J. Liu, M. C. Murphy, R. W. Mann (1997) A comparison of lower-extremity skeletal kinematics measured using skin- and pin-mounted markers. 16(2–3), 219–242. https://doi.org/10.1016/S0167-9457(96)00053-X
S. Tashman, K. DuPre, H. Goitz, T. Lock, P. Kolowich, M. Flynn (1995) A digital radiographic system for determining 3D joint kinematics during movement.
S. Tashman, W. Anderst, P. Kolowich (2000) Severity of OA related to magnitude of dynamic instability in ACL-deficient dogs. 257.
H. J. Woltring (1980) Planar control in multi-camera calibration for 3-D gait studies. 13(1), 39–48. https://doi.org/10.1016/0021-9290(80)90006-8
N. W. John (2002) Volume Rendering. 35–41. https://doi.org/10.1007/978-3-642-59438-0_5
W. Schroeder, K. Martin, B. Lorensen (2006) The VTK Book.
D. LaRose, J. Bayouth, T. Kanade (2000) Transgraph: interactive intensity-based 2D/3D registration of x-ray and CT. 385–396. https://doi.org/10.1117/12.387700
G. Papaioannou (2024) Method for the control of collimation, penumbra, dynamic exposure, and dosage in a number of robotics-driven 2D radiology and 3D computer tomography and other multimodality imaging.
B. Clark (2017) Data Visualization Toolkit: Using JavaScript, Rails ^{TM} , and Postgres to Present Data and Geospatial Information.
W. O. Thompson, F. L. Thaete, F. H. Fu, S. F. Dye (1991) Tibial meniscal dynamics using three-dimensional reconstruction of magnetic resonance images. 19(3), 210–216. https://doi.org/10.1177/036354659101900302
J. G. Tamez-Pena, S. Totterman, K. J. Parker (1999) Kinematic analysis of musculoskeletal structures via volumetric MRI and unsupervised segmentation.
G. Papaioannou, C. Mitrogiannis, M. Schweitzer, N. Michailidis, M. Pappa, P. Khosravi, A. Karantanas, S. Starling, C. Ruberg (2025) Towards the Performance Characterization of a Robotic Multimodal Diagnostic Imaging System. 11, 147. https://doi.org/10.3390/jimaging11050147
(2024) ANSA BETA CAE systems software suite. https://www.beta-cae.com/
G. Papaioannou, C. Mitrogiannis, G. Nianios, G. Fiedler (2009) Tracking high speed arthrokinematics using a new and high resolution Biplane Dynamic Roentgen Stereogrammetric method. 2(A09), 66–85.
B. Preim, C. P. Botha (2013) Visual Computing for Medicine.
(2019) Computer Vision and Image Processing: Fundamentals and Applications.
M. K. Sonka, V. Hlavac, R. Boyle (2015) Image Processing, Analysis and Machine Vision.
(2020) Modern Optimization Methods for Science, Engineering and Technology.
S. Ghafurian, D. N. Metaxas, V. Tan, K. Li (2016) Fast generation of digitally reconstructed radiograph through an efficient preprocessing of ray attenuation values.
G. P. Penney, J. Weese, J. A. Little, P. Desmedt, D. L. G. Hill, D. J. hawkes (1998) A comparison of similarity measures for use in 2-D-3-D medical image registration. 17(4), 586–595. https://doi.org/10.1109/42.730403
W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. T. Flannery (2007) Numerical Recipes in C: The Art of Scientific Computing.
S. A. Banks, W. A. Hodge (1996) Accurate measurement of three-dimensional knee replacement kinematics using single-plane fluoroscopy. 43(6), 638–649. https://doi.org/10.1109/10.495283
W. J. Suntay, E. S. Grood, M. S. Hefzy, D. L. Butler, F. R. Noyes (1983) Error Analysis of a System for Measuring Three-Dimensional Joint Motion. 105(2), 127–135. https://doi.org/10.1115/1.3138396
P. Bourke The shortest line between two lines in 3D. http://www.swin.edu.au/astronomy/pborke/geometry/lineline3d/
J. J. Craig (2017) Introduction to Robotics Mechanics & Control.
T. R. Kane, P. W. Likins, D. A. Levinson (1983) Spacecraft Dynamics.
B. Siciliano, O. Khatib (2016) Springer Handbook of Robotics. https://doi.org/10.1007/978-3-319-32552-1
K. Sakhatskyi (2023) Stable perovskite single-crystal X-ray imaging detectors with single-photon sensitivity. 17(6), 510–517. https://doi.org/10.1038/s41566-023-01207-y
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.
