Determination of Flow Parameters of a Water Flow Around an AUV Body

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 enviro...

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Bibliographic Details
Published in:Robotics (Basel) 2019, Vol.8 (1), p.5
Main Authors: Hoth, Julian, Kowalczyk, Wojciech
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Autonomous underwater vehicles
Cathodic protection
Compasses
computational fluid dynamics
Disturbances
Flow velocity
learning algorithms
Localization
Machine learning
Marine environment
Military applications
navigation
Navigation systems
Neural networks
Parameters
Pressure distribution
Pressure sensors
Robots
Sensors
Support vector machines
Water flow
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Summary: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.
ISSN:2218-6581
2218-6581
DOI:10.3390/robotics8010005