{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:42:16Z","timestamp":1760402536757,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,27]],"date-time":"2020-01-27T00:00:00Z","timestamp":1580083200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001602","name":"Science Foundation Ireland","doi-asserted-by":"publisher","award":["12\/RC\/2302_P2","14\/SP\/2740"],"award-info":[{"award-number":["12\/RC\/2302_P2","14\/SP\/2740"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010661","name":"Horizon 2020","doi-asserted-by":"publisher","award":["731103"],"award-info":[{"award-number":["731103"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a docking station heave motion prediction method for dynamic remotely operated vehicle (ROV) docking, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). Due to the limited power onboard the subsea vehicle, high hydrodynamic drag forces, and inertia, work-class ROVs are often unable to match the heave motion of a docking station suspended from a surface vessel. Therefore, the docking relies entirely on the experience of the ROV pilot to estimate heave motion, and on human-in-the-loop ROV control. However, such an approach is not available for autonomous docking. To address this problem, an ANFIS-based method for prediction of a docking station heave motion is proposed and presented. The performance of the network was evaluated on real-world reference trajectories recorded during offshore trials in the North Atlantic Ocean during January 2019. The hardware used during the trials included a work-class ROV with a cage type TMS, deployed using an A-frame launch and recovery system.<\/jats:p>","DOI":"10.3390\/s20030693","type":"journal-article","created":{"date-parts":[[2020,1,27]],"date-time":"2020-01-27T11:41:57Z","timestamp":1580125317000},"page":"693","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Neuro-Fuzzy Dynamic Position Prediction for Autonomous Work-Class ROV Docking"],"prefix":"10.3390","volume":"20","author":[{"given":"Petar","family":"Trsli\u0107","sequence":"first","affiliation":[{"name":"Centre for Robotics &amp; Intelligent Systems, University of Limerick, V94 T9PX Limerick, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9692-239X","authenticated-orcid":false,"given":"Edin","family":"Omerdic","sequence":"additional","affiliation":[{"name":"Centre for Robotics &amp; Intelligent Systems, University of Limerick, V94 T9PX Limerick, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gerard","family":"Dooly","sequence":"additional","affiliation":[{"name":"Centre for Robotics &amp; Intelligent Systems, University of Limerick, V94 T9PX Limerick, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3601-9216","authenticated-orcid":false,"given":"Daniel","family":"Toal","sequence":"additional","affiliation":[{"name":"Centre for Robotics &amp; Intelligent Systems, University of Limerick, V94 T9PX Limerick, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"McLeod, D. (2010, January 20\u201323). Emerging capabilities for autonomous inspection repair and maintenance. Proceedings of the OCEANS 2010 MTS\/IEEE SEATTLE, Seattle, WA, USA.","DOI":"10.1109\/OCEANS.2010.5664441"},{"key":"ref_2","first-page":"68","article-title":"A Sliding Scale of Residency","volume":"44","author":"Maslin","year":"2019","journal-title":"Offshore Eng. Mag."},{"key":"ref_3","unstructured":"Society for Underwater Technology (2018). Resident E-ROV. UT3 Mag., 12-4, 30\u201337."},{"key":"ref_4","first-page":"50","article-title":"ROV in Residence","volume":"44","author":"MacDonald","year":"2019","journal-title":"Offshore Eng. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Trslic, P., Rossi, M., Sivcev, S., Dooly, G., Coleman, J., Omerdic, E., and Toal, D. (2018, January 22\u201325). Long term, inspection class ROV deployment approach for remote monitoring and inspection. Proceedings of the OCEANS 2018 MTS\/IEEE Charleston, Charleston, SC, USA.","DOI":"10.1109\/OCEANS.2018.8604814"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Albiez, J., Joyeux, S., Gaudig, C., Hilljegerdes, J., Kroffke, S., Schoo, C., Arnold, S., Mimoso, G., Alcantara, P., and Saback, R. (2015, January 19\u201322). FlatFish\u2014a compact subsea-resident inspection AUV. Proceedings of the OCEANS 2015 - MTS\/IEEE Washington, Washington, DC, USA.","DOI":"10.23919\/OCEANS.2015.7404442"},{"key":"ref_7","first-page":"68","article-title":"Steps Toward Freedom","volume":"44","author":"Maslin","year":"2019","journal-title":"Offshore Eng. Mag."},{"key":"ref_8","unstructured":"Furuholmen, M., Hanssen, A., Carter, R., Hatlen, K., and Siesjo, J. (2013, January 20\u201322). Resident Autonomous Underwater Vehicle Systems\u2013A Review of Drivers, Applications, and Integration Options for the Subsea Oil and Gas Market. Proceedings of the Offshore Mediterranean Conference and Exhibition, Ravenna, Italy."},{"key":"ref_9","unstructured":"Fahrni, L., Thies, P.R., Johanning, L., and Cowles, J. (2018, January 8\u201310). Scope and feasibility of autonomous robotic subsea intervention systems for offshore inspection, maintenance and repair. Proceedings of the Proceedings of the 3rd International Conference on Renewable Energies Offshore (RENEW 2018), Lisbon, Portugal."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.ifacol.2016.10.428","article-title":"Experimental testing of a cooperative ASV-ROV multi-agent system","volume":"49","author":"Conte","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_11","unstructured":"(2020, January 26). Trial proves autonomous ROV deployment capability. Available online: https:\/\/www.offshore-mag.com\/business-briefs\/equipment-engineering\/article\/16790676\/trial-proves-autonomous-rov-deployment-capability."},{"key":"ref_12","unstructured":"Chardard, Y., and Copros, T. (2002, January 19). Swimmer: Final sea demonstration of this innovative hybrid AUV\/ROV system. Proceedings of the 2002 Interntional Symposium on Underwater Technology (Cat. No.02EX556), Tokyo, Japan."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Johansson, B., Siesj\u00f6, J., and Furuholmen, M. (2010, January 20\u201323). Seaeye Sabertooth A Hybrid AUV\/ROV offshore system. Proceedings of the OCEANS 2010 MTS\/IEEE SEATTLE, Seattle, WA, USA.","DOI":"10.1109\/OCEANS.2010.5663842"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Hobson, B.W., McEwen, R.S., Erickson, J., Hoover, T., McBride, L., Shane, F., and Bellingham, J.G. (October, January 29). The Development and Ocean Testing of an AUV Docking Station for a 21\" AUV. Proceedings of the OCEANS 2007, Vancouver, BC, Canada.","DOI":"10.1109\/OCEANS.2007.4449318"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Allen, B., Austin, T., Forrester, N., Goldsborough, R., Kukulya, A., Packard, G., Purcell, M., and Stokey, R. (2006, January 18\u201321). Autonomous Docking Demonstrations with Enhanced REMUS Technology. Proceedings of the OCEANS 2006, Boston, MA, USA.","DOI":"10.1109\/OCEANS.2006.306952"},{"key":"ref_16","unstructured":"(2013). Guidelines for Installing ROV Systems on Vessels or Platforms, International Marine Contractors Association (IMCA)."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Liu, S., Xu, H., Lin, Y., and Gao, L. (2019). Visual Navigation for Recovering an AUV by Another AUV in Shallow Water. Sensors, 19.","DOI":"10.3390\/s19081889"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Yazdani, A., Sammut, K., Lammas, A., Clement, B., and Yakimenko, O.A. (2019, January 17\u201320). Cooperative Guidance System for AUV Docking with an Active Suspended Docking Station. Proceedings of the OCEANS 2019\u2013Marseille, Marseille, France.","DOI":"10.1109\/OCEANSE.2019.8867214"},{"key":"ref_19","first-page":"37","article-title":"A USV-Based Automated Launch and Recovery System for AUVs","volume":"42","author":"Sarda","year":"2017","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_20","unstructured":"Raspante, F. (2012, January 14\u201319). Underwater mobile docking of autonomous underwater vehicles. Proceedings of the 2012 Oceans, Hampton Roads, VA, USA."},{"key":"ref_21","unstructured":"Conte, G., Scaradozzi, D., Mannocchi, D., and Ciuccoli, N. (2017, January 25\u201330). Field Test of an Integrated ASV\/ROV Platform. Proceedings of the 27th International Ocean and Polar Engineering Conference, San Francisco, CA, USA."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"106840","DOI":"10.1016\/j.oceaneng.2019.106840","article-title":"Vision based autonomous docking for work class ROVs","volume":"196","author":"Trslic","year":"2020","journal-title":"Ocean Eng."},{"key":"ref_23","unstructured":"Christ, R.D., and Wernli, R.L. (2014). The ROV Manual: A User Guide for Remotely Operated Vehicles, Butterworth-Heinemann is an imprint of Elsevier. [2nd ed.]."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1109\/21.256541","article-title":"ANFIS: Adaptive-network-based fuzzy inference system","volume":"23","author":"Jang","year":"1993","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1109\/41.808014","article-title":"Fuzzy predictive filters in model predictive control","volume":"46","author":"Setnes","year":"1999","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Das, V.V., Thomas, G., and Lumban Gaol, F. (2011). Efficient Object Motion Prediction Using Adaptive Fuzzy Navigational Environment. Information Technology and Mobile Communication, Springer.","DOI":"10.1007\/978-3-642-20573-6"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Sivcev, S., Trslic, P., Adley, D., Robinson, L., Dooly, G., Omerdic, E., and Toal, D. (2019, January 27\u201331). Adaptive Neuro-Fuzzy Network Enhanced Automatic Visual Servoing Algorithm for ROV Manipulators. Proceedings of the OCEANS 2019 MTS\/IEEE SEATTLE, Seattle, WA, USA.","DOI":"10.23919\/OCEANS40490.2019.8962868"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"7908","DOI":"10.1016\/j.eswa.2010.04.045","article-title":"An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange","volume":"37","author":"Boyacioglu","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref_29","first-page":"63","article-title":"Short Term Electricity Price Forecasting by Hybrid Mutual Information ANFIS-PSO Approach","volume":"10","author":"Yaser","year":"2019","journal-title":"Comput. Intell. Electr. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2263","DOI":"10.1007\/s10462-017-9610-2","article-title":"Adaptive network based fuzzy inference system (ANFIS) training approaches: A comprehensive survey","volume":"52","author":"Karaboga","year":"2019","journal-title":"Artif. Intell. Rev."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Shoorehdeli, M.A., Teshnehlab, M., and Sedigh, A.K. (2007, January 23\u201326). Novel Hybrid Learning Algorithms for Tuning ANFIS Parameters Using Adaptive Weighted PSO. Proceedings of the 2007 IEEE International Fuzzy Systems Conference, London, UK.","DOI":"10.1109\/FUZZY.2007.4295571"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/j.asoc.2007.03.010","article-title":"A novel approach for ANFIS modelling based on full factorial design","volume":"8","author":"Buragohain","year":"2008","journal-title":"Appl. Soft Comput."},{"key":"ref_33","unstructured":"Jang, J.S. (1996, January 11). Input selection for ANFIS learning. Proceedings of the IEEE 5th International Fuzzy Systems, New Orleans, LA, USA."},{"key":"ref_34","unstructured":"(2019, December 20). Vessel Schedules | Marine Institute. Home Page. Available online: http:\/\/www.marine.ie\/Home\/site-area\/infrastructure-facilities\/research-vessels\/vessel-schedules?language=ga."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Omerdic, E., and Toal, D. (2012, January 3\u20136). OceanRINGS: System concept and applications. Proceedings of the 2012 20th Mediterranean Conference on Control & Automation (MED), Barcelona, Spain.","DOI":"10.1109\/MED.2012.6265833"},{"key":"ref_36","unstructured":"Gal, O. (2013). OceanRINGS: Smart Technologies for Subsea Operations. Advanced in Marine Robotics, Lambert Acadmic Publishing. Chapter 11."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/3\/693\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:44:43Z","timestamp":1760363083000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/3\/693"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,27]]},"references-count":36,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["s20030693"],"URL":"https:\/\/doi.org\/10.3390\/s20030693","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,1,27]]}}}