{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T14:06:35Z","timestamp":1771164395063,"version":"3.50.1"},"reference-count":52,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Field Robotics"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Underwater inspections of critical maritime infrastructures are still predominantly performed by human divers, exposing them to safety risks and yielding limited accuracy and repeatability. Autonomous Underwater Vehicles (AUVs) offer a promising alternative by removing humans from hazardous environments and enabling systematic, repeatable inspection operations. However, current AUV systems lack the necessary autonomy and typically rely on prior knowledge of the environment, limiting their applicability in real\u2010world scenarios. This study presents a visual\u2013acoustic\u2010based framework aimed at overcoming these limitations and moving a step closer to fully autonomous inspection operations using AUVs. Designed for cost\u2010effective deployment on vehicles equipped with a minimal sensor suite\u2014including a stereo camera, an acoustic range sensor, an Inertial Measurement Unit with magnetometers, a pressure sensor, and a Global Positioning System (used only on the surface)\u2014the framework enables inspection of unknown underwater structures without human intervention. The main contribution lies in the integration of perception and navigation into a unified architecture, allowing the AUV to leverage the exteroceptive sensor not only for scene understanding but also to support real\u2010time control and mission adaptation. Perception data are combined with proprioceptive observations to adapt motion based on the environment, enabling autonomous management of the inspection mission and navigation with respect to the target. Furthermore, a mission manager coordinates all phases of the operation, from initial approach to structure\u2010relative navigation and visual data acquisition. The proposed solution was validated through a sea trial, during which an AUV autonomously inspected a harbor pier. The framework computed control actions in quasi\u2010real\u2010time to maintain a predefined safety distance, inspection velocity, and payload orientation orthogonal to the scene. These outputs were used online as feedback within the AUV's control loop. The underwater robot completed the inspection, maintaining mission references and ensuring effective target coverage, good\u2010quality optical data, and consistent three\u2010dimensional reconstruction. Overall, this experimental validation demonstrates the feasibility of the proposed framework and marks a significant milestone toward the deployment of fully autonomous AUVs for real\u2010world underwater inspection missions, even in the absence of prior knowledge about the structure.<\/jats:p>","DOI":"10.1002\/rob.70075","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T07:27:54Z","timestamp":1759217274000},"page":"1152-1177","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Visual\u2013Acoustic\u2010Based Framework for Online Inspection of Submerged Structures Using Autonomous Underwater Vehicles"],"prefix":"10.1002","volume":"43","author":[{"given":"Simone","family":"Tani","sequence":"first","affiliation":[{"name":"Department of Information Engineering University of Pisa Pisa Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3500-7133","authenticated-orcid":false,"given":"Francesco","family":"Ruscio","sequence":"additional","affiliation":[{"name":"Department of Information Engineering University of Pisa Pisa Italy"}]},{"given":"Andrea","family":"Caiti","sequence":"additional","affiliation":[{"name":"Department of Information Engineering University of Pisa Pisa Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8600-1976","authenticated-orcid":false,"given":"Riccardo","family":"Costanzi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering University of Pisa Pisa Italy"}]}],"member":"311","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2014.10.004"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8594445"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/Oceans-Spain.2011.6003474"},{"key":"e_1_2_8_5_1","first-page":"805","volume-title":"Chapter 27\u2014ROV Intervention and Interface","author":"Bai Y.","year":"2019"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2007.09.014"},{"key":"e_1_2_8_7_1","unstructured":"Bresciani M.2023. \u201cAutonomous Marine Vehicles: Improving Autonomy Through Cooperation.\u201d PhD thesis University of Pisa.https:\/\/tesidottorato.depositolegale.it\/handle\/20.500.14242\/216645."},{"key":"e_1_2_8_8_1","volume-title":"External Corrosion Control and Inspection of Deepwater Pipelines","author":"Britton J.","year":"2001"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-022-10071-8"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/3477.956031"},{"key":"e_1_2_8_11_1","volume-title":"Marine Control Systems\u2014Guidance, Navigation, and Control of Ships, Rigs and Underwater Vehicles","author":"Fossen T. 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