{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T06:05:42Z","timestamp":1771308342674,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T00:00:00Z","timestamp":1771027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["52275016"],"award-info":[{"award-number":["52275016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Science and Technology Development Fund Project on Central Government Guiding Local Government","award":["236Z1806G"],"award-info":[{"award-number":["236Z1806G"]}]},{"name":"Science and Technology Development Fund Project on Central Government Guiding Local Government","award":["226Z1801G"],"award-info":[{"award-number":["226Z1801G"]}]},{"name":"Science Research Project of the Hebei Education Department","award":["CXY2024052"],"award-info":[{"award-number":["CXY2024052"]}]},{"name":"Science Research Project of the Hebei Education Department","award":["JZX2023015"],"award-info":[{"award-number":["JZX2023015"]}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"crossref","award":["F2024202081"],"award-info":[{"award-number":["F2024202081"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>To meet the requirements for the automatic alignment, insertion, and inspection of guide-tube opening pins on the upper core plate in a component pool during refueling outages of nuclear power units, this paper proposes a cognition-enhanced visual-servoing framework that integrates geometric cognition-based compensation, observation-confidence modeling, and constraint-aware optimal control. The framework addresses the key challenge posed by the coexistence of long-term geometric drift and underwater observation uncertainty. Specifically, historical closed-loop data are leveraged to learn and compensate for systematic geometric errors online, substantially improving coarse-positioning accuracy. In addition, an explicit confidence model is introduced to quantitatively assess the reliability of visual measurements. Building on these components, a confidence-driven, finite-horizon, constrained model predictive control strategy is designed to achieve safe and efficient finite-step convergence while strictly respecting actuator physical constraints. Ground experiments and deep-water component-pool validations demonstrate that the proposed method reduces coarse-positioning error by approximately 75%, achieves stable sub-millimeter alignment with an ample engineering safety margin, and effectively decreases erroneous insertions and the need for manual intervention. These results confirm the engineering applicability and safety advantages of the proposed cognition-enhanced visual-servoing framework for underwater alignment tasks in nuclear component pools.<\/jats:p>","DOI":"10.3390\/bdcc10020061","type":"journal-article","created":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T14:09:54Z","timestamp":1771250994000},"page":"61","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Underwater Visual-Servo Alignment Control Integrating Geometric Cognition Compensation and Confidence Assessment"],"prefix":"10.3390","volume":"10","author":[{"given":"Jinkun","family":"Li","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingyu","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minglu","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China"},{"name":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinbao","family":"Li","sequence":"additional","affiliation":[{"name":"Jinan FinDreams Battery Co., Ltd., Jinan 250000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"109121","DOI":"10.1016\/j.ress.2023.109121","article-title":"Prognosis of wear-out effect on of safety equipment reliability for nuclear power plants long-term safe operation","volume":"233","author":"Carlos","year":"2023","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"024001","DOI":"10.1115\/1.4042194","article-title":"Current status and future developments in nuclear-power industry of the world","volume":"5","author":"Pioro","year":"2019","journal-title":"J. Nucl. Eng. Radiat. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"044001","DOI":"10.1115\/1.4047927","article-title":"Current status of reactors deployment and small modular reactors development in the world","volume":"6","author":"Pioro","year":"2020","journal-title":"J. Nucl. Eng. Radiat. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"011001","DOI":"10.1115\/1.4029420","article-title":"Nuclear power as a basis for future electricity generation","volume":"1","author":"Pioro","year":"2015","journal-title":"J. Nucl. Eng. Radiat. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"102506","DOI":"10.1016\/j.aei.2024.102506","article-title":"Predictive maintenance system for high-end equipment in nuclear power plant under limited degradation knowledge","volume":"61","author":"Liu","year":"2024","journal-title":"Adv. Eng. Inform."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"110556","DOI":"10.1016\/j.anucene.2024.110556","article-title":"Research on fault diagnosis and fault location of nuclear power plant equipment","volume":"205","author":"Huang","year":"2024","journal-title":"Ann. Nucl. Energy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"100515","DOI":"10.1016\/j.egyai.2025.100515","article-title":"Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications","volume":"20","author":"Lyu","year":"2025","journal-title":"Energy AI"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"100555","DOI":"10.1016\/j.egyai.2025.100555","article-title":"Automating Monte Carlo simulations in nuclear engineering with domain knowledge-embedded large language model agents","volume":"21","author":"Ndum","year":"2025","journal-title":"Energy AI"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"117797","DOI":"10.1016\/j.engstruct.2024.117797","article-title":"Research on evaluation method of underwater image quality and performance of underwater structure defect detection model","volume":"306","author":"Huang","year":"2024","journal-title":"Eng. Struct."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"71","DOI":"10.20965\/jrm.2024.p0071","article-title":"Integration of Multiple Sensors into an ROV for Remote Measurement in the Fukushima Daiichi Nuclear Power Station","volume":"36","author":"Kamada","year":"2024","journal-title":"J. Robot. Mechatron."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Nauert, F., and Kampmann, P. (2023). Inspection and maintenance of industrial infrastructure with autonomous underwater robots. Front. Robot. AI, 10.","DOI":"10.3389\/frobt.2023.1240276"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"113984","DOI":"10.1016\/j.ultramic.2024.113984","article-title":"Fourier transform-based post-processing drift compensation and calibration method for scanning probe microscopy","volume":"263","author":"Lutsyk","year":"2024","journal-title":"Ultramicroscopy"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"129292","DOI":"10.1016\/j.neucom.2024.129292","article-title":"SDI: A sparse drift identification approach for force\/torque sensor calibration in industrial robots","volume":"620","author":"Qiao","year":"2025","journal-title":"Neurocomputing"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3853","DOI":"10.1109\/TII.2021.3117034","article-title":"Visual and intelligent identification methods for defects in underwater structure using alternating current field measurement technique","volume":"18","author":"Yuan","year":"2021","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1109\/34.888718","article-title":"A flexible new technique for camera calibration","volume":"22","author":"Zhang","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8429099","DOI":"10.1155\/2023\/8429099","article-title":"Automatic detection of surface defects on underwater pile-pier of bridges based on image fusion and deep learning","volume":"2023","author":"Jiang","year":"2023","journal-title":"Struct. Control. Health Monit."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.jmsy.2024.08.027","article-title":"Data-driven unsupervised anomaly detection of manufacturing processes with multi-scale prototype augmentation and multi-sensor data","volume":"77","author":"Xie","year":"2024","journal-title":"J. Manuf. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"92020","DOI":"10.1109\/ACCESS.2019.2927413","article-title":"Unscented particle filter for online total image Jacobian matrix estimation in robot visual servoing","volume":"7","author":"Wang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"102685","DOI":"10.1016\/j.rcim.2023.102685","article-title":"A local POE-based self-calibration method using position and distance constraints for collaborative robots","volume":"86","author":"He","year":"2024","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"121501","DOI":"10.1016\/j.oceaneng.2025.121501","article-title":"A comprehensive review of datasets and deep learning techniques for vision in unmanned surface vehicles","volume":"334","author":"Trinh","year":"2025","journal-title":"Ocean Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"105786","DOI":"10.1016\/j.dsp.2025.105786","article-title":"Dynamic Feature Fusion Algorithm for Multi-Scale Biological Target Detection in Underwater Environments","volume":"170","author":"Song","year":"2025","journal-title":"Digit. Signal Process."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"116019","DOI":"10.1016\/j.oceaneng.2023.116019","article-title":"PCD reconstruction, object classification and pose estimation for underwater vehicles using orthogonal multibeam forward looking sonar fusion","volume":"288","author":"Sadjoli","year":"2023","journal-title":"Ocean Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.rcim.2010.06.013","article-title":"Robust Jacobian matrix estimation for image-based visual servoing","volume":"27","author":"Kosmopoulos","year":"2011","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2328","DOI":"10.1109\/TMECH.2023.3235902","article-title":"Position-based visual servo control of dual robotic arms with unknown kinematic models: A cerebellum-inspired approach","volume":"28","author":"Yu","year":"2023","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"17830","DOI":"10.1109\/ACCESS.2025.3534098","article-title":"Advancing underwater vision: A survey of deep learning models for underwater object recognition and tracking","volume":"13","author":"Elmezain","year":"2025","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ji, Y., Wang, J., Gong, Y., Zhang, L., Zhu, Y., Wang, H., Zhang, J., Sakai, T., and Yang, Y. (2023, January 17\u201324). Map: Multimodal uncertainty-aware vision-language pre-training model. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada.","DOI":"10.1109\/CVPR52729.2023.02228"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3212","DOI":"10.1109\/TIP.2024.3393365","article-title":"Quality-aware selective fusion network for VDT salient object detection","volume":"33","author":"Bao","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cja.2021.03.027","article-title":"Positioning error compensation of an industrial robot using neural networks and experimental study","volume":"35","author":"Li","year":"2022","journal-title":"Chin. J. Aeronaut."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"015020","DOI":"10.1088\/1361-6501\/ad00d3","article-title":"A method for compensating random errors in MEMS gyroscopes based on interval empirical mode decomposition and ARMA","volume":"35","author":"Zeng","year":"2023","journal-title":"Meas. Sci. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1016\/j.jfranklin.2021.11.009","article-title":"A survey of learning-based control of robotic visual servoing systems","volume":"359","author":"Wu","year":"2022","journal-title":"J. Frankl. Inst."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gabrielsen, T.A.L., Imsland, L.S., and Gros, S.N. (2025). Advanced Real-Time Iterations and Short-Horizon Predictor for Fast Nonlinear Model Predictive Control. 2025 IEEE Conference on Control Technology and Applications (CCTA), IEEE.","DOI":"10.1109\/CCTA53793.2025.11151412"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s00245-005-0829-y","article-title":"Remarks on risk-sensitive control problems","volume":"52","author":"Menaldi","year":"2005","journal-title":"Appl. Math. Optim."}],"container-title":["Big Data and Cognitive Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2504-2289\/10\/2\/61\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T05:14:48Z","timestamp":1771305288000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-2289\/10\/2\/61"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,14]]},"references-count":32,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["bdcc10020061"],"URL":"https:\/\/doi.org\/10.3390\/bdcc10020061","relation":{},"ISSN":["2504-2289"],"issn-type":[{"value":"2504-2289","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,14]]}}}