2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) 2017
DOI: 10.1109/robio.2017.8324478
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An accurate cavitation prediction thruster model based on Gaussian process regression

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Cited by 2 publications
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“…Luo et al used Gaussian process regression, which considers the cavitation effect, to create a thruster model. They have been verified the effectiveness of this model they created with proof-of-concept experiments, and the results of these experiments showed that the proposed model had fewer errors than the traditional model [3]. Gungor has been modeled the flow noise produced by an underwater vehicle in digital environment using LES (Large Edge Simulation).…”
Section: Introductionmentioning
confidence: 99%
“…Luo et al used Gaussian process regression, which considers the cavitation effect, to create a thruster model. They have been verified the effectiveness of this model they created with proof-of-concept experiments, and the results of these experiments showed that the proposed model had fewer errors than the traditional model [3]. Gungor has been modeled the flow noise produced by an underwater vehicle in digital environment using LES (Large Edge Simulation).…”
Section: Introductionmentioning
confidence: 99%
“…[1][2][3][4][5] Particularly, HITUWV (Underwater Welding Vehicle by Harbin Institute of Technology) is a UV which can complete automatic welding in spent fuel pools (SFPs). [6][7][8][9] Due to the centroid variations caused by the movements of the welding system on board, it is of great significance to develop a compensation controller for the HITUWV to complete automatic underwater welding with high accuracy and stability.…”
Section: Introductionmentioning
confidence: 99%