{"id":1214,"date":"2021-09-14T12:10:42","date_gmt":"2021-09-14T11:10:42","guid":{"rendered":"https:\/\/babel.isa.uma.es\/kipr\/?p=1214"},"modified":"2021-09-14T12:10:42","modified_gmt":"2021-09-14T11:10:42","slug":"a-possibly-interesting-paper-on-the-estimation-and-adaptation-of-ekf-slam-to-actual-models-of-the-system-and-the-noise-that-i-have-been-unable-to-read-due-to-its-painful-syntax","status":"publish","type":"post","link":"https:\/\/babel.isa.uma.es\/kipr\/?p=1214","title":{"rendered":"A possibly interesting paper on the estimation and adaptation of EKF-SLAM to actual models of the system and the noise that I have been unable to read due to its painful syntax"},"content":{"rendered":"<h4>Yingzhong Tian, Heru Suwoyo, Wenbin Wang, Dziki Mbemba, Long Li, <strong>An AEKF-SLAM Algorithm with Recursive Noise Statistic Based on MLE and EM,<\/strong> Journal of Intelligent &#038; Robotic Systems (2020) 97:339\u2013355, <a href=\"https:\/\/doi.org\/10.1007\/s10846-019-01044-8\" target=\"_blank\">DOI: 10.1007\/s10846-019-01044-8<\/a>.<\/h4>\n<blockquote><p>Extended Kalman Filter (EKF) has been popularly utilized for solving Simultaneous Localization and Mapping (SLAM)<br \/>\nproblem. Essentially, it requires the accurate system model and known noise statistic. Nevertheless, this condition can<br \/>\nbe satisfied in simulation case. Hence, EKF has to be enhanced when it is applied in the real-application. Mainly, this<br \/>\nimprovement is known as adaptive-based approach. In many different cases, it is indicated by some manners of estimating<br \/>\nfor either part or full noise statistic. This paper present a proposed method based on the adaptive-based solution used for<br \/>\nimproving classical EKF namely An Adaptive Extended Kalman Filter. Initially, the classical EKF was improved based on<br \/>\nMaximum Likelihood Estimation (MLE) and Expectation-Maximization (EM) Creation. It aims to equips the conventional<br \/>\nEKF with ability of approximating noise statistic and its covariance matrices recursively. Moreover, EKF was modified and<br \/>\nimproved to tune the estimated values given by MLE and EM creation. Besides that, the recursive noise statistic estimators<br \/>\nwere also estimated based on the unbiased estimation. Although it results high quality solution but it is followed with some<br \/>\nrisks of non-positive definite matrices of the process and measurement noise statistic covariances. Thus, an addition of<br \/>\nInnovation Covariance Estimation (ICE) was also utilized to depress this possibilities. The proposed method is applied for<br \/>\nsolving SLAM problem of autonomous wheeled mobile robot. Henceforth, it is termed as AEKF-SLAM Algorithm. In order<br \/>\nto validate the effectiveness of proposed method, some different SLAM-Based algorithm were compared and analyzed.<br \/>\nThe different simulation has been showing that the proposed method has better stability and accuracy compared to the<br \/>\nconventional filter in term of Root Mean Square Error (RMSE) of Estimated Map Coordinate (EMC) and Estimated Path<br \/>\nCoordinate (EPC).<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Yingzhong Tian, Heru Suwoyo, Wenbin Wang, Dziki Mbemba, Long Li, An AEKF-SLAM Algorithm with Recursive Noise Statistic Based on MLE <span class=\"ellipsis\">&hellip;<\/span> <span class=\"more-link-wrap\"><a href=\"https:\/\/babel.isa.uma.es\/kipr\/?p=1214\" class=\"more-link\"><span>Read More &rarr;<\/span><\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[430,131],"class_list":["post-1214","post","type-post","status-publish","format-standard","hentry","category-mobile-robot-slam","tag-adaptive-filtering","tag-ekf"],"_links":{"self":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1214"}],"collection":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1214"}],"version-history":[{"count":2,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1214\/revisions"}],"predecessor-version":[{"id":1216,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1214\/revisions\/1216"}],"wp:attachment":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1214"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1214"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1214"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}