{"title":"Object Tracking with Sensor Fusion – An Interactive Learning Tool","authors":"Andrei Moraru , Eva-H. Dulf","doi":"10.1016/j.ifacol.2024.10.285","DOIUrl":null,"url":null,"abstract":"<div><div>Body tracking plays a key role in autonomous navigation applications. Behavior that resists inertia can be modelled as a dynamical system, wherein the kinematic component is constituted by the action of motion. Such a system may then be subjected to estimation algorithms and control laws formulated by systems theory, according to the specific problem domain for which it is modelled. This paper presents a detailed comparison of three main statistical algorithms for estimating dynamical system parameters: the linear, extended, and unscented Kalman filters. The body motion is intercepted by sensor fusion. To facilitate visual validation and concretization of the theoretical notions presented, a two-dimensional (2D) game-like graphical application has been developed to enhance user comprehension.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 26","pages":"Pages 142-145"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC-PapersOnLine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405896324020603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
Body tracking plays a key role in autonomous navigation applications. Behavior that resists inertia can be modelled as a dynamical system, wherein the kinematic component is constituted by the action of motion. Such a system may then be subjected to estimation algorithms and control laws formulated by systems theory, according to the specific problem domain for which it is modelled. This paper presents a detailed comparison of three main statistical algorithms for estimating dynamical system parameters: the linear, extended, and unscented Kalman filters. The body motion is intercepted by sensor fusion. To facilitate visual validation and concretization of the theoretical notions presented, a two-dimensional (2D) game-like graphical application has been developed to enhance user comprehension.
期刊介绍：
All papers from IFAC meetings are published, in partnership with Elsevier, the IFAC Publisher, in theIFAC-PapersOnLine proceedings series hosted at the ScienceDirect web service. This series includes papers previously published in the IFAC website.The main features of the IFAC-PapersOnLine series are: -Online archive including papers from IFAC Symposia, Congresses, Conferences, and most Workshops. -All papers accepted at the meeting are published in PDF format - searchable and citable. -All papers published on the web site can be cited using the IFAC PapersOnLine ISSN and the individual paper DOI (Digital Object Identifier). The site is Open Access in nature - no charge is made to individuals for reading or downloading. Copyright of all papers belongs to IFAC and must be referenced if derivative journal papers are produced from the conference papers. All papers published in IFAC-PapersOnLine have undergone a peer review selection process according to the IFAC rules.
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