{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T09:50:44Z","timestamp":1777715444796,"version":"3.51.4"},"reference-count":28,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T00:00:00Z","timestamp":1697500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil (CAPES)","award":["001"],"award-info":[{"award-number":["001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Some advantages of using cameras as sensor devices on feedback systems are the flexibility of the data it represents, the possibility to extract real-time information, and the fact that it does not require contact to operate. However, in unstructured scenarios, Image-Based Visual Servoing (IBVS) robot tasks are challenging. Camera calibration and robot kinematics can approximate a jacobian that maps the image features space to the robot actuation space, but they can become error-prone or require online changes. Uncalibrated visual servoing (UVS) aims at executing visual servoing tasks without previous camera calibration or through camera model uncertainties. One way to accomplish that is through jacobian identification using environment information in an estimator, such as the Kalman filter. The Kalman filter is optimal with Gaussian noise, but unstructured environments may present target occlusion, reflection, and other characteristics that confuse feature extraction algorithms, generating outliers. This work proposes RMCKF, a correntropy-induced estimator based on the Kalman Filter and the Maximum Correntropy Criterion that can handle non-Gaussian feature extraction noise. Unlike other approaches, we designed RMCKF for particularities in UVS, to deal with independent features, the IBVS control action, and simulated annealing. We designed Monte Carlo experiments to test RMCKF with non-Gaussian Kalman Filter-based techniques. The results showed that the proposed technique could outperform its relatives, especially in impulsive noise scenarios and various starting configurations.<\/jats:p>","DOI":"10.3390\/s23208518","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T08:25:09Z","timestamp":1697531109000},"page":"8518","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Regularized Maximum Correntropy Criterion Kalman Filter for Uncalibrated Visual Servoing in the Presence of Non-Gaussian Feature Tracking Noise"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8886-6348","authenticated-orcid":false,"given":"Glauber Rodrigues","family":"Leite","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, Center of Technology, Federal University of Rio Grande do Norte\u2014UFRN, Natal 59072-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6769-4946","authenticated-orcid":false,"given":"\u00cdcaro Bezerra Queiroz de","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Computing Institute, A. C. Sim\u00f5es Campus, Federal University of Alagoas\u2014UFAL, Macei\u00f3 57072-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9486-4509","authenticated-orcid":false,"given":"Allan de Medeiros","family":"Martins","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Center of Technology, Federal University of Rio Grande do Norte\u2014UFRN, Natal 59072-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"113816","DOI":"10.1016\/j.eswa.2020.113816","article-title":"Self-driving cars: A survey","volume":"165","author":"Badue","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"012036","DOI":"10.1088\/1742-6596\/1267\/1\/012036","article-title":"Common Sensors in Industrial Robots: A Review","volume":"1267","author":"Li","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_3","unstructured":"Brock, O., Park, J., and Toussaint, M. (2016). Springer Handbook of Robotics, Springer."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1007\/s00138-013-0570-5","article-title":"Thermal cameras and applications: A survey","volume":"25","author":"Gade","year":"2014","journal-title":"Mach. Vis. Appl."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1111\/cgf.13386","article-title":"State of the art on 3D reconstruction with RGB-D cameras","volume":"37","author":"Zollhofer","year":"2018","journal-title":"Comput. Graph. Forum"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1324","DOI":"10.1007\/s12555-018-0753-y","article-title":"Adaptive Switch Image-based Visual Servoing for Industrial Robots","volume":"18","author":"Ghasemi","year":"2020","journal-title":"Int. J. Control. Autom. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Li, J., Huang, H., Xu, Y., Wu, H., and Wan, L. (2019). Uncalibrated visual servoing for underwater vehicle manipulator systems with an eye in hand configuration camera. Sensors, 19.","DOI":"10.3390\/s19245469"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1007\/s10846-023-01827-0","article-title":"Fully Automatic Visual Servoing Control for Underwater Vehicle Manipulator Systems Based on a Heuristic Inverse Kinematics","volume":"107","author":"Santos","year":"2023","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Bahnemann, R., Schindler, D., Kamel, M., Siegwart, R., and Nieto, J. (2017, January 11\u201313). A Decentralized Multi-Agent Unmanned Aerial System to Search, Pick Up, and Relocate Objects. Proceedings of the 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), Shanghai, China.","DOI":"10.1109\/SSRR.2017.8088150"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Voros, S., Long, J.A., and Cinquin, P. (2006, January 1\u20136). Automatic Localization of Laparoscopic Instruments for the Visual Servoing of an Endoscopic Camera Holder. Proceedings of the Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2006, Copenhagen, Denmark.","DOI":"10.1007\/11866565_66"},{"key":"ref_11","unstructured":"Forsyth, D.A., and Ponce, J. (2011). Computer Vision: A Modern Approach, Prentice Hall. [2nd ed.]."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Corke, P. (2017). Robotics, Vision and Control, Springer International Publishing. Springer Tracts in Advanced Robotics.","DOI":"10.1007\/978-3-319-54413-7"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Szeliski, R. (2022). Computer Vision, Springer International Publishing. [2nd ed.]. Texts in Computer Science.","DOI":"10.1007\/978-3-030-34372-9"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Shahria, M.T., Sunny, M.S.H., Zarif, M.I.I., Ghommam, J., Ahamed, S.I., and Rahman, M.H. (2022). A Comprehensive Review of Vision-Based Robotic Applications: Current State, Components, Approaches, Barriers, and Potential Solutions. Robotics, 11.","DOI":"10.3390\/robotics11060139"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"10652","DOI":"10.1109\/JIOT.2019.2940412","article-title":"Toward Accurate Vehicle State Estimation Under Non-Gaussian Noises","volume":"6","author":"Xiao","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.automatica.2016.10.004","article-title":"Maximum correntropy Kalman filter","volume":"76","author":"Chen","year":"2017","journal-title":"Automatica"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Izanloo, R., Fakoorian, S.A., Yazdi, H.S., and Simon, D. (2016, January 15\u201318). Kalman filtering based on the maximum correntropy criterion in the presence of non-Gaussian noise. Proceedings of the 2016 Annual Conference on Information Science and Systems (CISS), Princeton, NJ, USA.","DOI":"10.1109\/CISS.2016.7460553"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1002\/asjc.1865","article-title":"Sequential Maximum Correntropy Kalman Filtering","volume":"22","author":"Kulikova","year":"2020","journal-title":"Asian J. Control"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1016\/j.ifacol.2021.04.200","article-title":"Uncalibrated Image-Based Visual Servoing Control with Maximum Correntropy Kalman Filter","volume":"53","author":"Xiaolin","year":"2020","journal-title":"IFAC-PapersOnLine"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ramirez, O.A., and Jagersand, M. (2016, January 1\u20133). Practical considerations of uncalibrated visual servoing. Proceedings of the 2016 13th Conference on Computer and Robot Vision (CRV 2016), Victoria, BC, Canada.","DOI":"10.1109\/CRV.2016.44"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A New Approach to Linear Filtering and Prediction Problems","volume":"82","author":"Kalman","year":"1960","journal-title":"J. Basic Eng."},{"key":"ref_22","unstructured":"Choset, H., Lynch, K., Hutchinson, S., and Kantor, G. (2005). Principles of Robot Motion, MIT Press."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"842","DOI":"10.4304\/jcp.7.4.842-845","article-title":"Robot Visual Servo with Fuzzy Particle Filter","volume":"7","author":"Ma","year":"2012","journal-title":"J. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Shademan, A., Farahmand, A.m., and Jagersand, M. (2010, January 3\u20138). Robust Jacobian estimation for uncalibrated visual servoing. Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK, USA.","DOI":"10.1109\/ROBOT.2010.5509911"},{"key":"ref_25","unstructured":"Erdogmus, D., and Liu, W. (2010). Information Theoretic Learning: Renyi\u2019s Entropy and Kernel Perspectives, Springer New York."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1080\/01621459.1976.10480344","article-title":"A method for simulating stable random variables","volume":"71","author":"Chambers","year":"1976","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_27","unstructured":"Weron, A., and Weron, R. (1995). Chaos\u2014The Interplay Between Stochastic and Deterministic Behaviour, Springer Berlin Heidelberg."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Leite, G., Araujo, I., and Martins, A. (2023, September 06). Dataset: Regularized Maximum-Correntropy Criterion Kalman Filter for Uncalibrated Visual Servoing in the Presence of Non-Gaussian Feature Tracking Noise. Figshare. Collection. Available online: https:\/\/figshare.com\/collections\/Regularized_Maximum-Correntropy_Criterion_Kalman_Filter_for_uncalibrated_visual_servoing_in_the_presence_of_non-gaussian_feature_tracking_noise\/6724320.","DOI":"10.3390\/s23208518"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/20\/8518\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:08:21Z","timestamp":1760130501000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/20\/8518"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,17]]},"references-count":28,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2023,10]]}},"alternative-id":["s23208518"],"URL":"https:\/\/doi.org\/10.3390\/s23208518","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,17]]}}}