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A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion

A matrix information-geometric method was developed to detect the change-points of rigid body motions. Note that the set of all rigid body motions is the special Euclidean group [Formula: see text] , so the Riemannian mean based on the Lie group structures of [Formula: see text] reflects the charact...

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Detalles Bibliográficos
Autores principales: Duan, Xiaomin, Sun, Huafei, Zhao, Xinyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515020/
https://www.ncbi.nlm.nih.gov/pubmed/33267245
http://dx.doi.org/10.3390/e21050531
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author Duan, Xiaomin
Sun, Huafei
Zhao, Xinyu
author_facet Duan, Xiaomin
Sun, Huafei
Zhao, Xinyu
author_sort Duan, Xiaomin
collection PubMed
description A matrix information-geometric method was developed to detect the change-points of rigid body motions. Note that the set of all rigid body motions is the special Euclidean group [Formula: see text] , so the Riemannian mean based on the Lie group structures of [Formula: see text] reflects the characteristics of change-points. Once a change-point occurs, the distance between the current point and the Riemannian mean of its neighbor points should be a local maximum. A gradient descent algorithm is proposed to calculate the Riemannian mean. Using the Baker–Campbell–Hausdorff formula, the first-order approximation of the Riemannian mean is taken as the initial value of the iterative procedure. The performance of our method was evaluated by numerical examples and manipulator experiments.
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spelling pubmed-75150202020-11-09 A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion Duan, Xiaomin Sun, Huafei Zhao, Xinyu Entropy (Basel) Article A matrix information-geometric method was developed to detect the change-points of rigid body motions. Note that the set of all rigid body motions is the special Euclidean group [Formula: see text] , so the Riemannian mean based on the Lie group structures of [Formula: see text] reflects the characteristics of change-points. Once a change-point occurs, the distance between the current point and the Riemannian mean of its neighbor points should be a local maximum. A gradient descent algorithm is proposed to calculate the Riemannian mean. Using the Baker–Campbell–Hausdorff formula, the first-order approximation of the Riemannian mean is taken as the initial value of the iterative procedure. The performance of our method was evaluated by numerical examples and manipulator experiments. MDPI 2019-05-25 /pmc/articles/PMC7515020/ /pubmed/33267245 http://dx.doi.org/10.3390/e21050531 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Duan, Xiaomin
Sun, Huafei
Zhao, Xinyu
A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion
title A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion
title_full A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion
title_fullStr A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion
title_full_unstemmed A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion
title_short A Matrix Information-Geometric Method for Change-Point Detection of Rigid Body Motion
title_sort matrix information-geometric method for change-point detection of rigid body motion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515020/
https://www.ncbi.nlm.nih.gov/pubmed/33267245
http://dx.doi.org/10.3390/e21050531
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