Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.2109
This item is licensed with a CreativeCommons licence https://creativecommons.org/licenses/by/4.0/
Publisher DOI: 10.3390/robotics8010005
Title: Determination of flow parameters of a water flow around an AUV body
Language: English
Authors: Hoth, Julian  
Kowalczyk, Wojciech 
Keywords: navigation;learning algorithms;computational fluid dynamics;autonomous underwater vehicles
Issue Date: 28-Jan-2019
Publisher: Multidisciplinary Digital Publishing Institute
Source: Robotics 8 (1): 5 (2019)
Journal or Series Name: Robotics 
Abstract (english): Autonomous underwater vehicles (AUVs) have changed the way marine environment is surveyed, monitored and mapped. Autonomous underwater vehicles have a wide range of applications in research, military, and commercial settings. AUVs not only perform a given task but also adapt to changes in the environment, e.g., sudden side currents, downdrafts, and other effects which are extremely unpredictable. To navigate properly and allow simultaneous localisation and mapping (SLAM) algorithms to be used, these effects need to be detected. With current navigation systems, these disturbances in the water flow are not measured directly. Only the indirect effects are observed. It is proposed to detect the disturbances directly by placing pressure sensors on the surface of the AUV and processing the pressure data obtained. Within this study, the applicability of different learning methods for determining flow parameters of a surrounding fluid from pressure on an AUV body are tested. This is based on CFD simulations using pressure data from specified points on the surface of the AUV. It is shown that support vector machines are most suitable for the given task and yield excellent results.
URI: http://hdl.handle.net/11420/2229
DOI: 10.15480/882.2109
ISSN: 2218-6581
Other Identifiers: doi: 10.3390/robotics8010005
Institute: Zentrum für Lehre und Lernen (ZLL) 
Type: (wissenschaftlicher) Artikel
Appears in Collections:Publications (tub.dok)

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