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Shape Estimation for Elongated Deformable Object using B-spline Chained Multiple Random Matrices ModelIn this paper, a B-spline chained multiple random matrix models (RMMs) representation is proposed to model geometric characteristics of an elongated deformable object. The hyper degrees of freedom structure of the elongated deformable object make its shape estimation challenging. Based on the likelihood function of the proposed B-spline chained multiple RMMs, an expectation-maximization (EM) method is derived to estimate the shape of the elongated deformable object. A split and merge method based on the Euclidean minimum spanning tree (EMST) is proposed to provide initialization for the EM algorithm. The proposed algorithm is evaluated for the shape estimation of the elongated deformable objects in scenarios, such as the static rope with various configurations (including configurations with intersection), the continuous manipulation of a rope and a plastic tube, and the assembly of two plastic tubes. The execution time is computed and the accuracy of the shape estimation results is evaluated based on the comparisons between the estimated width values and its ground-truth, and the intersection over union (IoU) metric.
Document ID
20240003635
Acquisition Source
2230 Support
Document Type
Accepted Manuscript (Version with final changes)
Authors
Gang Yao
(University of Connecticut Groton, United States)
Ryan Saltus ORCID
(University of Connecticut Storrs, Connecticut, United States)
Ashwin P. Dani ORCID
(University of Connecticut Storrs, Connecticut, United States)
Date Acquired
March 26, 2024
Publication Date
November 7, 2020
Publication Information
Publication: International Journal of Intelligent Robotics and Applications
Publisher: Springer Nature (United States)
Volume: 4
Issue Publication Date: December 1, 2020
ISSN: 2366-5971
e-ISSN: 2366-598X
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Funding Number(s)
CONTRACT_GRANT: 80NSSC19K1076
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
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