{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T16:36:39Z","timestamp":1776443799224,"version":"3.51.2"},"reference-count":51,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T00:00:00Z","timestamp":1708387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Defence, Poland"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Autonomous Underwater Vehicles (AUVs) are currently one of the most intensively developing branches of marine technology. Their widespread use and versatility allow them to perform tasks that, until recently, required human resources. One problem in AUVs is inadequate navigation, which results in inaccurate positioning. Weaknesses in electronic equipment lead to errors in determining a vehicle\u2019s position during underwater missions, requiring periodic reduction of accumulated errors through the use of radio navigation systems (e.g., GNSS). However, these signals may be unavailable or deliberately distorted. Therefore, in this paper, we propose a new computer vision-based method for estimating the position of an AUV. Our method uses computer vision and deep learning techniques to generate the surroundings of the vehicle during temporary surfacing at the point where it is currently located. The next step is to compare this with the shoreline representation on the map, which is generated for a set of points that are in a specific vicinity of a point determined by dead reckoning. This method is primarily intended for low-cost vehicles without advanced navigation systems. Our results suggest that the proposed solution reduces the error in vehicle positioning to 30\u201360 m and can be used in incomplete shoreline representations. Further research will focus on the use of the proposed method in fully autonomous navigation systems.<\/jats:p>","DOI":"10.3390\/rs16050741","type":"journal-article","created":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T11:50:07Z","timestamp":1708429807000},"page":"741","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Computer Vision-Based Position Estimation for an Autonomous Underwater Vehicle"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8258-0181","authenticated-orcid":false,"given":"Jacek","family":"Zalewski","sequence":"first","affiliation":[{"name":"Faculty of Mechanical and Electrical Engineering, Polish Naval Academy, 81-127 Gdynia, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1422-0330","authenticated-orcid":false,"given":"Stanis\u0142aw","family":"Ho\u017cy\u0144","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical and Electrical Engineering, Polish Naval Academy, 81-127 Gdynia, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.oceaneng.2019.04.011","article-title":"Advancements in the field of autonomous underwater vehicle","volume":"181","author":"Sahoo","year":"2019","journal-title":"Ocean Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.arcontrol.2006.08.003","article-title":"Autonomous underwater vehicles for scientific and naval operations","volume":"30","author":"Bovio","year":"2006","journal-title":"Annu. Rev. Control"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Joochim, C., Phadungthin, R., and Srikitsuwan, S. (2015, January 18\u201320). Design and development of a Remotely Operated Underwater Vehicle. Proceedings of the 2015 16th International Conference on Research and Education in Mechatronics (REM), Bochum, Germany.","DOI":"10.1109\/REM.2015.7380385"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1177\/0020294020952483","article-title":"A review of different designs and control models of remotely operated underwater vehicle","volume":"53","author":"He","year":"2020","journal-title":"Meas. Control"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Maurelli, F., Krupi\u0144ski, S., Xiang, X., and Petillot, Y. (2021). AUV Localisation: A Review of Passive and Active Techniques, Springer.","DOI":"10.1007\/s41315-021-00215-x"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Xie, Y.x., Liu, J., Hu, C.q., Cui, J.h., and Xu, H. (2016, January 24\u201326). AUV Dead-Reckoning Navigation Based on Neural Network Using a Single Accelerometer. Proceedings of the 11th ACM International Conference on Underwater Networks & Systems, Shanghai, China.","DOI":"10.1145\/2999504.3001081"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1109\/TIV.2020.2980758","article-title":"AI-IMU Dead-Reckoning","volume":"5","author":"Brossard","year":"2020","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.ifacol.2016.10.334","article-title":"MEMS-based Inertial Navigation on Dynamically Positioned Ships: Dead Reckoning","volume":"49","author":"Rogne","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Chu, Z., Zhu, D., Sun, B., Nie, J., and Xue, D. (2015, January 3\u20136). Design of a dead reckoning based motion control system for small autonomous underwater vehicle. Proceedings of the 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), Halifax, NS, Canada.","DOI":"10.1109\/CCECE.2015.7129365"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"De Agostino, M., Manzino, A.M., and Piras, M. (2010, January 4\u20136). Performances comparison of different MEMS-based IMUs. Proceedings of the IEEE\/ION Position, Location and Navigation Symposium, Indian Wells, CA, USA.","DOI":"10.1109\/PLANS.2010.5507128"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Vitale, G., D\u2019Alessandro, A., Costanza, A., and Fagiolini, A. (2017, January 19\u201322). Low-cost underwater navigation systems by multi-pressure measurements and AHRS data. Proceedings of the OCEANS 2017, Aberdeen, UK.","DOI":"10.1109\/OCEANSE.2017.8084621"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.mee.2015.07.004","article-title":"Tactical grade MEMS vibrating ring gyroscope with high shock reliability","volume":"142","author":"Yoon","year":"2015","journal-title":"Microelectron. Eng."},{"key":"ref_13","unstructured":"Vickery, K. (1998, January 21). Acoustic positioning systems. A practical overview of current systems. Proceedings of the 1998 Workshop on Autonomous Underwater Vehicles (Cat. No.98CH36290), Cambridge, MA, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1109\/JOE.2017.2771898","article-title":"Modeling AUV Localization Error in a Long Baseline Acoustic Positioning System","volume":"43","author":"Thomson","year":"2018","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.apacoust.2016.04.009","article-title":"Underwater target localization using long baseline positioning system","volume":"111","author":"Zhang","year":"2016","journal-title":"Appl. Acoust."},{"key":"ref_16","unstructured":"Matos, A., Cruz, N., Martins, A., and Lobo Pereira, F. (1999, January 13\u201316). Development and implementation of a low-cost LBL navigation system for an AUV. Proceedings of the Oceans \u201999. MTS\/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No.99CH37008), Seattle, WA, USA."},{"key":"ref_17","unstructured":"Mandt, M., Gade, K., and Jalving, B. (2001, January 28\u201330). Integrating DGPS-USBL position measurements with inertial navigation in the HUGIN 3000 AUV. Proceedings of the 8th Saint Petersburg International Conference on Integrated Navigation Systems, Saint Petersburg, Russia."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1902","DOI":"10.1109\/JPROC.2008.2006090","article-title":"Evolution of the Global Navigation SatelliteSystem (GNSS)","volume":"96","author":"Hegarty","year":"2008","journal-title":"Proc. IEEE"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1002\/navi.291","article-title":"Introduction to BeiDou-3 navigation satellite system","volume":"66","author":"Yang","year":"2019","journal-title":"Navigation"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1109\/JOE.2012.2191996","article-title":"Instantaneous Global Navigation Satellite System (GNSS)-Based Attitude Determination for Maritime Applications","volume":"37","author":"Giorgi","year":"2012","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1017\/S0373463319000584","article-title":"Optimisation of the Position of Navigational Aids for the Purposes of SLAM technology for Accuracy of Vessel Positioning","volume":"73","author":"Marchel","year":"2020","journal-title":"J. Navig."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Karkus, P., Cai, S., and Hsu, D. (2021, January 19\u201325). Differentiable SLAM-Net: Learning Particle SLAM for Visual Navigation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA.","DOI":"10.1109\/CVPR46437.2021.00284"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1109\/JOE.2012.2235664","article-title":"Relocating Underwater Features Autonomously Using Sonar-Based SLAM","volume":"38","author":"Fallon","year":"2013","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Siantidis, K. (2016, January 6\u20139). Side scan sonar based onboard SLAM system for autonomous underwater vehicles. Proceedings of the 2016 IEEE\/OES Autonomous Underwater Vehicles (AUV), Tokyo, Japan.","DOI":"10.1109\/AUV.2016.7778671"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1109\/JOE.2018.2883887","article-title":"Coastal SLAM with Marine Radar for USV Operation in GPS-Restricted Situations","volume":"44","author":"Han","year":"2019","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ueland, E.S., Skjetne, R., and Dahl, A.R. (2017, January 25\u201330). Marine Autonomous Exploration Using a Lidar and SLAM, Volume 6: Ocean Space Utilization. Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering, Trondheim, Norway.","DOI":"10.1115\/OMAE2017-61880"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Hidalgo, F., and Braunl, T. (2015, January 17\u201319). Review of underwater SLAM techniques. Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications (ICARA), Queenstown, New Zealand.","DOI":"10.1109\/ICARA.2015.7081165"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Jung, J., Lee, Y., Kim, D., Lee, D., Myung, H., and Choi, H.T. (2017, January 21\u201324). AUV SLAM using forward\/downward looking cameras and artificial landmarks. Proceedings of the 2017 IEEE Underwater Technology (UT), Busan, Republic of Korea.","DOI":"10.1109\/UT.2017.7890307"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1186\/s41074-017-0027-2","article-title":"Visual SLAM algorithms: A survey from 2010 to 2016","volume":"9","author":"Taketomi","year":"2017","journal-title":"IPSJ Trans. Comput. Vis. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1109\/TRO.2008.918049","article-title":"Toward a Unified Bayesian Approach to Hybrid Metric\u2013Topological SLAM","volume":"24","author":"Blanco","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1036","DOI":"10.1109\/TRO.2007.903811","article-title":"Convergence and Consistency Analysis for Extended Kalman Filter Based SLAM","volume":"23","author":"Huang","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Naus, K., and Marchel, L. (2019). Use of a Weighted ICP Algorithm to Precisely Determine USV Movement Parameters. Appl. Sci., 9.","DOI":"10.3390\/app9173530"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Stateczny, A., Kazimierski, W., Burdziakowski, P., Motyl, W., and Wisniewska, M. (2019). Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8020080"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"333","DOI":"10.5194\/isprs-archives-XLII-2-W6-333-2017","article-title":"Ultralight radar for small and micro-uav navigation","volume":"42","author":"Scannapieco","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1002\/rob.20371","article-title":"360-degree visual detection and target tracking on an autonomous surface vehicle","volume":"27","author":"Wolf","year":"2010","journal-title":"J. Field Robot."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"00012","DOI":"10.1051\/e3sconf\/20186300012","article-title":"The concept of anti-collision system of autonomous surface vehicle","volume":"63","author":"Stateczny","year":"2018","journal-title":"E3S Web Conf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/rob.20380","article-title":"Stereo vision\u2013based navigation for autonomous surface vessels","volume":"28","author":"Huntsberger","year":"2011","journal-title":"J. Field Robot."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ho\u017cy\u0144, S., and Zak, B. (2021). Stereo Vision System for Vision-Based Control of Inspection-Class ROVs. Remote Sens., 13.","DOI":"10.3390\/rs13245075"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.oceaneng.2017.01.024","article-title":"Stereovision-based target tracking system for USV operations","volume":"133","author":"Sinisterra","year":"2017","journal-title":"Ocean Eng."},{"key":"ref_40","first-page":"47","article-title":"Accuracy in fixing ship\u2019s positions by CCD camera survey of horizontal angles","volume":"5","author":"Naus","year":"2011","journal-title":"Geomat. Environ. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1002\/rob.20246","article-title":"Robust vision-based underwater homing using self-similar landmarks","volume":"25","author":"Negre","year":"2008","journal-title":"J. Field Robot."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.oceaneng.2008.10.001","article-title":"Experiments on vision guided docking of an autonomous underwater vehicle using one camera","volume":"36","author":"Park","year":"2009","journal-title":"Ocean Eng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1993","DOI":"10.1109\/TITS.2016.2634580","article-title":"Video Processing From Electro-Optical Sensors for Object Detection and Tracking in a Maritime Environment: A Survey","volume":"18","author":"Prasad","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1109\/TRO.2015.2424032","article-title":"Visual Navigation Using Heterogeneous Landmarks and Unsupervised Geometric Constraints","volume":"31","author":"Lu","year":"2015","journal-title":"IEEE Trans. Robot."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1109\/ACCESS.2019.2961762","article-title":"Visual Navigation Features Selection Algorithm Based on Instance Segmentation in Dynamic Environment","volume":"8","author":"Mu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Moskalenko, V., Moskalenko, A., Korobov, A., and Semashko, V. (2019). The Model and Training Algorithm of Compact Drone Autonomous Visual Navigation System. Data, 4.","DOI":"10.3390\/data4010004"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Zhan, W., Xiao, C., Wen, Y., Zhou, C., Yuan, H., Xiu, S., Zou, X., Xie, C., and Li, Q. (2020). Adaptive Semantic Segmentation for Unmanned Surface Vehicle Navigation. Electronics, 9.","DOI":"10.3390\/electronics9020213"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Hozyn, S., and Zalewski, J. (2020). Shoreline Detection and Land Segmentation for Autonomous Surface Vehicle Navigation with the Use of an Optical System. Sensors, 20.","DOI":"10.3390\/s20102799"},{"key":"ref_49","unstructured":"Commons, W. (2022, July 26). File: Calculating How Much of a Distant Object Is Visible above the Horizon.jpg\u2014Wikimedia Commons, the Free Media Repository. Available online: https:\/\/commons.wikimedia.org\/wiki\/File:Calculating_How_Much_of_a_Distant_Object_is_Visible_Above_the_Horizon.jpg."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"106062","DOI":"10.1016\/j.knosys.2020.106062","article-title":"Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey","volume":"201\u2013202","author":"Sultana","year":"2020","journal-title":"Knowl. Based Syst."},{"key":"ref_51","first-page":"74","article-title":"Image Segmentation Using Deep Learning: A Survey","volume":"44","author":"Minaee","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/5\/741\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:01:51Z","timestamp":1760104911000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/5\/741"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,20]]},"references-count":51,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["rs16050741"],"URL":"https:\/\/doi.org\/10.3390\/rs16050741","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,20]]}}}