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Underwater spatial field monitoring with small scale robots: an experimental study
Citation Link: https://doi.org/10.15480/882.13531
Publikationstyp
Conference Paper
Date Issued
2024-09-18
Sprache
English
Author(s)
TORE-DOI
Start Page
107
End Page
114
Citation
35. Forum Bauinformatik, fbi 2024: 107-114
Contribution to Conference
Publisher
Technische Universität Hamburg, Institut für Digitales und Autonomes Bauen
Peer Reviewed
true
Autonomous underwater vehicles (AUVs) can serve as efficient and cost-effective mobile sensor nodes for monitoring of underwater environments and construction sites such as marinas or nuclear storage ponds. In field exploration, the information collected by the AUV is used to construct a probabilistic field belief model of the environmental field. This can then be used to integrate an information metric into the path planning step. In this paper, a Gaussian Process-based field belief for a scalar, 2D underwater environmental field is investigated. The main contribution is the extensive experimental validation using real measurements. For testing purposes, a radiation field is mimicked using electro-magnetic carrier signals emitted by spatially distributed active beacons. Leveraging the attenuation of these signals underwater, the AUV measures the received signal strength. In literature so far, field exploration frameworks in the underwater domain are typically validated in experiments by simulating the field itself and the resulting measurements. While sensor noise can be integrated relatively easily, this still constitutes an over-simplification due to model imperfections. Moreover, this approach neglects other effects resulting from e.g. dynamic motion as the AUV interacts with the environment or field anomalies due to obstacles. Hence, an experimental investigation under realistic conditions is expected to deliver insights.
Subjects
Gaussian Process regression
Probabilistic field modeling
underwater robotics
DDC Class
500: Science
621.8: Machine Engineering
519: Applied Mathematics, Probabilities
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Underwater Spatial Field Monitoring with Small Scale Robots An Experimental Study.pdf
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