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Underwater Robotics - Fluid Parameter Identification for Modelling of Underwater Snake Robots

Authors: Elgenes, Gard Farstad; Kilvær, Henrik;

Underwater Robotics - Fluid Parameter Identification for Modelling of Underwater Snake Robots

Abstract

Unmanned underwater vehicles are being increasingly used for subsea maintenance, inspection and repair. Development of underwater snake robots show promising results towards extending the capabilities of traditional unmanned underwater vehicles. The slender and multi-articulated body of underwater snake robots allow for operation in tight spaces where other traditional underwater vehicles are incapable of operating. The modelling and the control of underwater snake robots brings extra challenges compared to the traditional underwater vehicles, and thus it is important to develop accurate models to ensure desired behaviour and to precisely investigate the locomotion efficiency. A key component is the hydrodynamic modelling, taking into account complex and non-linear hydrodynamic effects. These hydrodynamic effects are difficult to model and are often based on analytical estimates. This thesis seeks to determine the drag and added mass coefficients of a general planar model of underwater snake robots. The thesis presents methods for identifying fluid parameters based on CFD simulations and several experimental approaches. Additionally, this thesis investigates variations of the drag force modelling, providing more accurate representations of the hydrodynamic drag forces. The obtained fluid coefficients are compared to the existing estimates of fluid coefficients for a general model of underwater snake robots.

Keywords

Kybernetikk og robotikk (2 årig)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green