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A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation
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dc.contributor.author Kim, Taehoon -
dc.contributor.author Jeong, Juwon -
dc.contributor.author Kong, Taejune -
dc.contributor.author Lee, Hyunwook -
dc.contributor.author Oh, Sehoon -
dc.date.accessioned 2025-01-20T20:10:16Z -
dc.date.available 2025-01-20T20:10:16Z -
dc.date.created 2024-08-08 -
dc.date.issued 2024-06-19 -
dc.identifier.isbn 9798350394085 -
dc.identifier.issn 2163-5145 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/57556 -
dc.description.abstract EffiDynaMix, a novel, efficient, gray-box, nonparametric dynamics modeling method, integrates mathematical dynamics with Gaussian Mixture Model (GMM) for simplified training data creation and improved generalization. It outperforms traditional methods like conv-GMM, GP, and LSTM in training efficiency and accuracy with new data. By leveraging dynamic equations, EffiDynaMix enhances learning efficiency and adaptability, offering advancements in robotic system precision and computational efficiency, leading to faster and more responsive robots. © 2024 IEEE. -
dc.language English -
dc.publisher IEEE Industrial Electronics Society -
dc.relation.ispartof IEEE International Symposium on Industrial Electronics -
dc.title A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation -
dc.type Conference Paper -
dc.identifier.doi 10.1109/ISIE54533.2024.10595794 -
dc.identifier.wosid 001290477100116 -
dc.identifier.scopusid 2-s2.0-85199606329 -
dc.identifier.bibliographicCitation Kim, Taehoon. (2024-06-19). A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation. 33rd IEEE International Symposium on Industrial Electronics, ISIE 2024, 1–4. doi: 10.1109/ISIE54533.2024.10595794 -
dc.identifier.url https://ieee-isie-2024.org/conference-program -
dc.citation.conferenceDate 2024-06-18 -
dc.citation.conferencePlace KO -
dc.citation.conferencePlace 울산 -
dc.citation.endPage 4 -
dc.citation.startPage 1 -
dc.citation.title 33rd IEEE International Symposium on Industrial Electronics, ISIE 2024 -
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오세훈
Oh, Sehoon오세훈

Department of Robotics and Mechatronics Engineering

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