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This work presents a pose-graph SLAM and calibration framework specifically designed for 3D profiling sonars, such as the Coda Octopus Echoscope 3D. The system integrates a probabilistic scan matching method (3DupIC) for direct registration of 3D sonar scans, enabling accurate trajectory and map estimation even under degraded dead reckoning conditions. Unlike other bathymetric SLAM methods that rely on submaps and assume short-term localization accuracy, the proposed approach performs direct scan-to-scan registration, removing this dependency. The factor graph is extended to represent the sonar extrinsic parameters, allowing the sonar-to-body transformation to be refined jointly with trajectory optimization. Experimental validation on a challenging real world dataset demonstrates outstanding localization and mapping performance. The use of refined extrinsic parameters further improves both accuracy and map consistency, confirming the effectiveness of the proposed joint SLAM and calibration approach for robust and consistent underwater mapping.<\/jats:p>","DOI":"10.3390\/rs18030524","type":"journal-article","created":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T15:24:19Z","timestamp":1770305059000},"page":"524","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Underwater SLAM and Calibration with a 3D Profiling Sonar"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6091-1549","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Ferreira","sequence":"first","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5844-5393","authenticated-orcid":false,"given":"Jos\u00e9","family":"Almeida","sequence":"additional","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"ISEP\u2014School of Engineering, Polytechnic Institute of Porto, Rua Dr. Ant\u00f3nio Bernardino de Almeida, 431, 4249-015 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9771-002X","authenticated-orcid":false,"given":"An\u00edbal","family":"Matos","sequence":"additional","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"FEUP\u2014Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7166-3459","authenticated-orcid":false,"given":"Eduardo","family":"Silva","sequence":"additional","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"ISEP\u2014School of Engineering, Polytechnic Institute of Porto, Rua Dr. Ant\u00f3nio Bernardino de Almeida, 431, 4249-015 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1109\/MRA.2019.2908063","article-title":"Underwater Robots: From Remotely Operated Vehicles to Intervention-Autonomous Underwater Vehicles","volume":"26","author":"Petillot","year":"2019","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"113861","DOI":"10.1016\/j.oceaneng.2023.113861","article-title":"Autonomous Underwater Vehicle navigation: A review","volume":"273","author":"Zhang","year":"2023","journal-title":"Ocean Eng."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Vallicrosa, G., Himri, K., Ridao, P., and Gracias, N. (2021). Semantic Mapping for Autonomous Subsea Intervention. Sensors, 21.","DOI":"10.3390\/s21206740"},{"key":"ref_4","unstructured":"Aulinas, J., Petillot, Y., Salvi, J., and Llad\u00f3, X. (2008). The SLAM Problem: A Survey. Conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence, IOS Press."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s43154-022-00096-3","article-title":"Perception for Underwater Robots","volume":"3","author":"McConnell","year":"2022","journal-title":"Curr. Robot. Rep."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1729881420904526","DOI":"10.1177\/1729881420904526","article-title":"Real-time GNSS precise positioning: RTKLIB for ROS","volume":"17","author":"Ferreira","year":"2020","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Almeida, J., Ferreira, A., Matias, B., Lomba, C., Martins, A., and Silva, E. (2018). \u00a1VAMOS! Underwater Mining Machine Navigation System. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 1\u20135 October 2018, IEEE.","DOI":"10.1109\/IROS.2018.8593773"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1616","DOI":"10.1109\/JOE.2024.3507824","article-title":"Hybrid Long\/Inverted Ultra-Short Baseline (LBL-iUSBL) Acoustic Pose Estimation for Underwater Sonar Mapping","volume":"50","author":"Rypkema","year":"2025","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Almeida, J., Matias, B., Ferreira, A., Almeida, C., Martins, A., and Silva, E. (2020). Underwater Localization System Combining iUSBL with Dynamic SBL in \u00a1VAMOS! Trials. Sensors, 20.","DOI":"10.3390\/s20174710"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Macario Barros, A., Michel, M., Moline, Y., Corre, G., and Carrel, F. (2022). A Comprehensive Survey of Visual SLAM Algorithms. Robotics, 11.","DOI":"10.3390\/robotics11010024"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, X., Fan, X., Shi, P., Ni, J., and Zhou, Z. (2023). An Overview of Key SLAM Technologies for Underwater Scenes. Remote Sens., 15.","DOI":"10.3390\/rs15102496"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"100510","DOI":"10.1016\/j.cosrev.2022.100510","article-title":"Visual SLAM for underwater vehicles: A survey","volume":"46","author":"Zhang","year":"2022","journal-title":"Comput. Sci. Rev."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Heshmat, M., Saad Saoud, L., Abujabal, M., Sultan, A., Elmezain, M., Seneviratne, L., and Hussain, I. (2025). Underwater SLAM Meets Deep Learning: Challenges, Multi-Sensor Integration, and Future Directions. Sensors, 25.","DOI":"10.3390\/s25113258"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Vallicrosa, G., and Ridao, P. (2018). H-SLAM: Rao-Blackwellized Particle Filter SLAM Using Hilbert Maps. Sensors, 18.","DOI":"10.3390\/s18051386"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Hansen, R.K., and Andersen, P.A. (1996). A 3D Underwater Acoustic Camera\u2014Properties and Applications. Acoustical Imaging, Springer.","DOI":"10.1007\/978-1-4419-8772-3_98"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Martins, A., Almeida, J., Almeida, C., Matias, B., Kapusniak, S., and Silva, E. (2018). EVA a Hybrid ROV\/AUV for Underwater Mining Operations Support. Proceedings of the 2018 OCEANS\u2014MTS\/IEEE Kobe Techno-Oceans (OTO), Kobe, Japan, 28\u201331 May 2018, IEEE.","DOI":"10.1109\/OCEANSKOBE.2018.8558880"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ferreira, A., Almeida, J., Martins, A., Matos, A., and Silva, E. (2022). 3DupIC: An Underwater Scan Matching Method for Three-Dimensional Sonar Registration. Sensors, 22.","DOI":"10.3390\/s22103631"},{"key":"ref_18","first-page":"1793","article-title":"Autonomous underwater simultaneous localisation and map building","volume":"Volume 2","author":"Williams","year":"2000","journal-title":"Proceedings of the 2000 ICRA, Millennium Conference, IEEE International Conference on Robotics and Automation, Symposia Proceedings (Cat. No.00CH37065), San Francisco, CA, USA, 24\u201328 April 2000"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1002\/rob.20249","article-title":"Underwater SLAM in man-made structured environments","volume":"25","author":"Ribas","year":"2008","journal-title":"J. Field Robot."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"377","DOI":"10.3182\/20100906-3-IT-2019.00066","article-title":"Underwater Scan Matching using a Mechanical Scanned Imaging Sonar","volume":"43","author":"Oliver","year":"2010","journal-title":"IFAC Proc. Vol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5024","DOI":"10.1109\/JSEN.2015.2432082","article-title":"Improving Localization Accuracy for an Underwater Robot with a Slow-Sampling Sonar Through Graph Optimization","volume":"15","author":"Chen","year":"2015","journal-title":"IEEE Sens. J."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Johannsson, H., Kaess, M., Englot, B., Hover, F., and Leonard, J. (2010). Imaging sonar-aided navigation for autonomous underwater harbor surveillance. Proceedings of the 2010 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18\u201322 October 2010, IEEE.","DOI":"10.1109\/IROS.2010.5650831"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1016","DOI":"10.1109\/TRO.2013.2260952","article-title":"On 3-D Motion Estimation From Feature Tracks in 2-D FS Sonar Video","volume":"29","author":"Negahdaripour","year":"2013","journal-title":"IEEE Trans. Robot."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Huang, T.A., and Kaess, M. (2015). Towards acoustic structure from motion for imaging sonar. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 28 September\u20133 October 2015, IEEE.","DOI":"10.1109\/IROS.2015.7353457"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2330","DOI":"10.1109\/LRA.2018.2809510","article-title":"Pose-Graph SLAM Using Forward-Looking Sonar","volume":"3","author":"Li","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/JOE.2024.3458108","article-title":"Large-Scale Dense 3-D Mapping Using Submaps Derived From Orthogonal Imaging Sonars","volume":"50","author":"McConnell","year":"2025","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.oceaneng.2017.04.047","article-title":"Survey on advances on terrain based navigation for autonomous underwater vehicles","volume":"139","author":"Melo","year":"2017","journal-title":"Ocean Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/rob.20165","article-title":"Real-Time SLAM with Octree Evidence Grids for Exploration in Underwater Tunnels","volume":"24","author":"Fairfield","year":"2007","journal-title":"J. Field Robot."},{"key":"ref_29","unstructured":"Montemerlo, M., Thrun, S., Koller, D., and Wegbreit, B. (2002). FastSLAM: A factored solution to the simultaneous localization and mapping problem. Proceedings of the Eighteenth National Conference on Artificial Intelligence, Edmonton, AB, Canada, 28 July\u20131 August 2002, American Association for Artificial Intelligence."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1109\/MRA.2006.1678144","article-title":"Simultaneous localization and mapping: Part I","volume":"13","author":"Bailey","year":"2006","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1002\/rob.20382","article-title":"A featureless approach to efficient bathymetric SLAM using distributed particle mapping","volume":"28","author":"Barkby","year":"2011","journal-title":"J. Field Robot."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1177\/0278364912459666","article-title":"Bathymetric particle filter SLAM using trajectory maps","volume":"31","author":"Barkby","year":"2012","journal-title":"Int. J. Robot. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"85464","DOI":"10.1109\/ACCESS.2021.3088541","article-title":"Bathymetric Particle Filter SLAM with Graph-Based Trajectory Update Method","volume":"9","author":"Zhang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"26318","DOI":"10.1109\/ACCESS.2018.2830819","article-title":"A Multibeam-Based SLAM Algorithm for Iceberg Mapping Using AUVs","volume":"6","author":"Norgren","year":"2018","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3150","DOI":"10.1109\/LRA.2023.3264750","article-title":"Online Stochastic Variational Gaussian Process Mapping for Large-Scale Bathymetric SLAM in Real Time","volume":"8","author":"Torroba","year":"2023","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_36","unstructured":"Eliazar, A., and Parr, R. (2003). DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks. Proceedings of the 18th International Joint Conference on Artificial Intelligence, Acapulco, Mexico, 9\u201315 August 2003, Morgan Kaufmann Publishers Inc."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Fairfield, N., and Wettergreen, D. (2009). Evidence grid-based methods for 3D map matching. Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan, 12\u201317 May 2009, IEEE.","DOI":"10.1109\/ROBOT.2009.5152688"},{"key":"ref_38","unstructured":"Montemerlo, M., Thrun, S., Roller, D., and Wegbreit, B. (2003). FastSLAM 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges. Proceedings of the 18th International Joint Conference on Artificial Intelligence, IJCAI\u201903, San Francisco, CA, USA, 9\u201315 August 2003, Morgan Kaufmann Publishers Inc."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Grisetti, G., Stachniss, C., and Burgard, W. (2005). Improving Grid-based SLAM with Rao-Blackwellized Particle Filters By Adaptive Proposals and Selective Resampling. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, 18\u201322 April 2005, IEEE.","DOI":"10.1109\/ROBOT.2005.1570477"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/TRO.2006.889486","article-title":"Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters","volume":"23","author":"Grisetti","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zandara, S., Ridao, P., Ribas, D., Mallios, A., and Palomer, A. (2013). Probabilistic surface matching for bathymetry based SLAM. Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 6\u201310 May 2013, IEEE.","DOI":"10.1109\/ICRA.2013.6630554"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Palomer, A., Ridao, P., and Ribas, D. (2016). Multibeam 3D Underwater SLAM with Probabilistic Registration. Sensors, 16.","DOI":"10.3390\/s16040560"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Roman, C., and Singh, H. (2005). Improved vehicle based multibeam bathymetry using sub-maps and SLAM. Proceedings of the 2005 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Edmonton, AB, Canada, 2\u20136 August 2005, IEEE.","DOI":"10.1109\/IROS.2005.1545340"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1002\/rob.20164","article-title":"A Self-Consistent Bathymetric Mapping Algorithm","volume":"24","author":"Roman","year":"2007","journal-title":"J. Field Robot."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1109\/TRO.2016.2624754","article-title":"Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age","volume":"32","author":"Cadena","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"ref_46","first-page":"31","article-title":"A Tutorial on Graph-Based SLAM","volume":"2","author":"Grisetti","year":"2010","journal-title":"IEEE Intell. Transp. Syst. Mag."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1146\/annurev-control-061520-010504","article-title":"Factor Graphs: Exploiting Structure in Robotics","volume":"4","author":"Dellaert","year":"2021","journal-title":"Annu. Rev. Control. Robot. Auton. Syst."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Torroba, I., Bore, N., and Folkesson, J. (2019). Towards Autonomous Industrial-Scale Bathymetric Surveying. Proceedings of the 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 3\u20138 November 2019, IEEE.","DOI":"10.1109\/IROS40897.2019.8968241"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Bichucher, V., Walls, J.M., Ozog, P., Skinner, K.A., and Eustice, R.M. (2015). Bathymetric factor graph SLAM with sparse point cloud alignment. Proceedings of the OCEANS 2015\u2014MTS\/IEEE Washington, Washington, DC, USA, 19\u201322 October 2015, IEEE.","DOI":"10.23919\/OCEANS.2015.7404433"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Bore, N., Torroba, I., and Folkesson, J. (2018). Sparse Gaussian Process SLAM, Storage and Filtering for AUV Multibeam Bathymetry. Proceedings of the 2018 IEEE\/OES Autonomous Underwater Vehicle Workshop (AUV), Porto, Portugal, 6\u20139 November 2018, IEEE.","DOI":"10.1109\/AUV.2018.8729748"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1002\/rob.22272","article-title":"Underwater Pose SLAM using GMM scan matching for a mechanical profiling sonar","volume":"41","author":"Vial","year":"2024","journal-title":"J. Field Robot."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1109\/34.121791","article-title":"A method for registration of 3-D shapes","volume":"14","author":"Besl","year":"1992","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1016\/j.image.2005.02.003","article-title":"A complete system for on-line 3D modelling from acoustic images","volume":"20","author":"Castellani","year":"2005","journal-title":"Signal Process. Image Commun."},{"key":"ref_54","first-page":"3450","article-title":"Fast and Robust Iterative Closest Point","volume":"44","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Torroba, I., Bore, N., and Folkesson, J. (2018). A Comparison of Submap Registration Methods for Multibeam Bathymetric Mapping. Proceedings of the 2018 IEEE\/OES Autonomous Underwater Vehicle Workshop (AUV), Porto, Portugal, 6\u20139 November 2018, IEEE.","DOI":"10.1109\/AUV.2018.8729731"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"114779","DOI":"10.1016\/j.oceaneng.2023.114779","article-title":"A review of terrain aided navigation for underwater vehicles","volume":"281","author":"Ma","year":"2023","journal-title":"Ocean Eng."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Burguera, A., Gonzalez, Y., and Oliver, G. (2007). Probabilistic Sonar Scan Matching for Robust Localization. Proceedings of the 2007 IEEE International Conference on Robotics and Automation, Rome, Italy, 10\u201314 April 2007, IEEE.","DOI":"10.1109\/ROBOT.2007.363959"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Montesano, L., Minguez, J., and Montano, L. (2005). Probabilistic scan matching for motion estimation in unstructured environments. Proceedings of the 2005 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Edmonton, AB, Canada, 2\u20136 August 2005, IEEE.","DOI":"10.1109\/IROS.2005.1545182"},{"key":"ref_59","first-page":"3","article-title":"MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar","volume":"3","author":"Ridao","year":"2009","journal-title":"J. Phys. Agents"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Mallios, A., Ridao, P., Hernandez, E., Ribas, D., Maurelli, F., and Petillot, Y. (2009). Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar. Proceedings of the OCEANS 2009-EUROPE, Bremen, Germany, 11\u201314 May 2009, IEEE.","DOI":"10.1109\/OCEANSE.2009.5278219"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Burguera, A., Oliver, G., and Gonz\u00e0lez, Y. (2010). Scan-based SLAM with trajectory correction in underwater environments. Proceedings of the 2010 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18\u201322 October 2010, IEEE.","DOI":"10.1109\/IROS.2010.5649492"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Palomer, A., Ridao, P., Ribas, D., Mallios, A., Gracias, N., and Vallicrosa, G. (2013). Bathymetry-based SLAM with difference of normals point-cloud subsampling and probabilistic ICP registration. Proceedings of the 2013 MTS\/IEEE OCEANS, Bergen, Norway, 10\u201314 June 2013, IEEE.","DOI":"10.1109\/OCEANS-Bergen.2013.6608091"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Ferreira, A., Almeida, J., Matos, A., and Silva, E. (2025). Real-Time Registration of 3D Underwater Sonar Scans. Robotics, 14.","DOI":"10.3390\/robotics14020013"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Chaves, S.M., Galceran, E., Ozog, P., Walls, J.M., and Eustice, R.M. (2017). Pose-Graph SLAM for Underwater Navigation. Sensing and Control for Autonomous Vehicles: Applications to Land, Water and Air Vehicles, Springer International Publishing.","DOI":"10.1007\/978-3-319-55372-6_7"},{"key":"ref_65","unstructured":"Dellaert, F. (2012). Factor Graphs and GTSAM: A Hands-on Introduction, Georgia Institute of Technology."},{"key":"ref_66","unstructured":"K\u00fcmmerle, R., Grisetti, G., Strasdat, H., Konolige, K., and Burgard, W. (2011). G2o: A general framework for graph optimization. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, 9\u201313 May 2011, IEEE."},{"key":"ref_67","unstructured":"Agarwal, S., Mierle, K., and Team, T.C.S. (2026, February 01). Ceres Solver. Available online: https:\/\/github.com\/ceres-solver\/ceres-solver."},{"key":"ref_68","unstructured":"Sol\u00e0, J. (2017). Course on SLAM, Institut de Rob\u00f2tica i Inform\u00e0tica Industrial, CSIC-UPC. Technical Report IRI-TR-16-04."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1177\/0278364906072768","article-title":"Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing","volume":"25","author":"Dellaert","year":"2006","journal-title":"Int. J. Robot. Res."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Sol\u00e0, J., Deray, J., and Atchuthan, D. (2021). A micro Lie theory for state estimation in robotics. arXiv.","DOI":"10.21105\/joss.01371"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Roman, C., and Singh, H. (2006). Consistency based error evaluation for deep sea bathymetric mapping with robotic vehicles. Proceedings of the 2006 IEEE International Conference on Robotics and Automation, ICRA, Orlando, FL, USA, 15\u201319 May 2006, IEEE.","DOI":"10.1109\/ROBOT.2006.1642247"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/18\/3\/524\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T12:14:07Z","timestamp":1770725647000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/18\/3\/524"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,5]]},"references-count":71,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["rs18030524"],"URL":"https:\/\/doi.org\/10.3390\/rs18030524","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,5]]}}}