Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation

Authors
Kim, TaehoonJeong, JuwonKong, TaejuneLee, HyunwookOh, Sehoon
Issue Date
Jul-2024
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE International Symposium on Industrial Electronics
Indexed
SCOPUS
Journal Title
IEEE International Symposium on Industrial Electronics
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/73839
DOI
10.1109/ISIE54533.2024.10595794
ISSN
2163-5137
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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
ETC > Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher ,  photo

,
IT공과대학 (메카트로닉스공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE