Probabilistic Identification of Unmanned Surface Vehicles Using Efficient Gaussian Processes with Uncertainty Propagation-Reference-Cited by-同舟云学术

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Probabilistic Identification of Unmanned Surface Vehicles Using Efficient Gaussian Processes with Uncertainty Propagation

Published:2022-10-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Unmanned Systems (ICUS)
language:
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Author:

Xue Yifan¹,Wang Xingyao²,Qin Hongde³,Deng Zhongchao¹

Affiliation:

1. Harbin Engineering University,Qingdao Innovation and Development Base,Qingdao,China

2. Institute of Marine Science and Technology, Shandong University,Qingdao,China

3. Harbin Engineering University,Science and Technology on Underwater Vehicle Laboratory,Harbin,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9986510/9986514/09986638.pdf?arnumber=9986638

Reference29 articles.

1. Nonparametric Identification of Nonlinear Added Mass Moment of Inertia and Damping Moment Characteristics of Large-Amplitude Ship Roll Motion

2. Black-box models from input-output measurements

3. Large Tanker Motion Model Identification Using Generalized Ellipsoidal Basis Function-Based Fuzzy Neural Networks

4. Machine Learning for Fluid Mechanics

5. Measures to diminish the parameter drift in the modeling of ship manoeuvring using system identification

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