Multisensor fusion for marine infrastructures' inspection and safety

Vidya Sudevan; Nikita Mankovskii; Sajid Javed; Hamad Karki; Giulia De Masi; Jorge Dias

doi:10.1109/OCEANS47191.2022.9977154

Multisensor fusion for marine infrastructures' inspection and safety

Vidya Sudevan
, Nikita Mankovskii
, Sajid Javed
, Hamad Karki
, Giulia De Masi
, Jorge Dias

Autonomous Robotics Research Center

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Periodic inspection and maintenance of marine infrastructures are essential to ensure the safety and uninterrupted operation. Accurate localization and pose estimation of the remotely operating underwater vehicle is of prime importance to conduct any robotic marine intervention. A generic visual-inertial registration framework is proposed here to estimate the drift-free rotational and translational pose of the underwater vehicle that can be directly fed to the high level vehicle controller. Underwater image formation model based image enhancement technique along with the pose estimation module is the key of the proposed G-VINS algorithm. The theoretical formulation along with the experimental results shows the robustness and the applicability of the proposed method in marine environment characterized by different level of turbidity.

Original language	British English
Title of host publication	OCEANS 2022 Hampton Roads
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665468091
DOIs	https://doi.org/10.1109/OCEANS47191.2022.9977154
State	Published - 2022
Event	2022 OCEANS Hampton Roads, OCEANS 2022 - Hampton Roads, United States Duration: 17 Oct 2022 → 20 Oct 2022

Publication series

Name	Oceans Conference Record (IEEE)
Volume	2022-October
ISSN (Print)	0197-7385

Conference

Conference	2022 OCEANS Hampton Roads, OCEANS 2022
Country/Territory	United States
City	Hampton Roads
Period	17/10/22 → 20/10/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

image enhancement
marine infrastructure inspection
pose estimation
visual-inertial registration

Access to Document

10.1109/OCEANS47191.2022.9977154

OpenUrl availability

Full text

Cite this

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title = "Multisensor fusion for marine infrastructures' inspection and safety",

abstract = "Periodic inspection and maintenance of marine infrastructures are essential to ensure the safety and uninterrupted operation. Accurate localization and pose estimation of the remotely operating underwater vehicle is of prime importance to conduct any robotic marine intervention. A generic visual-inertial registration framework is proposed here to estimate the drift-free rotational and translational pose of the underwater vehicle that can be directly fed to the high level vehicle controller. Underwater image formation model based image enhancement technique along with the pose estimation module is the key of the proposed G-VINS algorithm. The theoretical formulation along with the experimental results shows the robustness and the applicability of the proposed method in marine environment characterized by different level of turbidity.",

keywords = "image enhancement, marine infrastructure inspection, pose estimation, visual-inertial registration",

author = "Vidya Sudevan and Nikita Mankovskii and Sajid Javed and Hamad Karki and Masi, \{Giulia De\} and Jorge Dias",

note = "Funding Information: G.D.M. and N.M. acknowledge the project “Heterogeneous Swarm of Underwater Autonomous Vehicles” funded by the Technology Innovation Institute (Abu Dhabi) developed with Khalifa University (contract no. TII/ARRC/2047/2020). Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 OCEANS Hampton Roads, OCEANS 2022 ; Conference date: 17-10-2022 Through 20-10-2022",

year = "2022",

doi = "10.1109/OCEANS47191.2022.9977154",

language = "British English",

series = "Oceans Conference Record (IEEE)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "OCEANS 2022 Hampton Roads",

address = "United States",

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Sudevan, V, Mankovskii, N, Javed, S , Karki, H, Masi, GD & Dias, J 2022, Multisensor fusion for marine infrastructures' inspection and safety. in OCEANS 2022 Hampton Roads. Oceans Conference Record (IEEE), vol. 2022-October, Institute of Electrical and Electronics Engineers Inc., 2022 OCEANS Hampton Roads, OCEANS 2022, Hampton Roads, United States, 17/10/22. https://doi.org/10.1109/OCEANS47191.2022.9977154

Multisensor fusion for marine infrastructures' inspection and safety. / Sudevan, Vidya; Mankovskii, Nikita; Javed, Sajid et al.
OCEANS 2022 Hampton Roads. Institute of Electrical and Electronics Engineers Inc., 2022. (Oceans Conference Record (IEEE); Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Mankovskii, Nikita

AU - Javed, Sajid

AU - Karki, Hamad

AU - Masi, Giulia De

AU - Dias, Jorge

N1 - Funding Information: G.D.M. and N.M. acknowledge the project “Heterogeneous Swarm of Underwater Autonomous Vehicles” funded by the Technology Innovation Institute (Abu Dhabi) developed with Khalifa University (contract no. TII/ARRC/2047/2020). Publisher Copyright: © 2022 IEEE.

PY - 2022

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AB - Periodic inspection and maintenance of marine infrastructures are essential to ensure the safety and uninterrupted operation. Accurate localization and pose estimation of the remotely operating underwater vehicle is of prime importance to conduct any robotic marine intervention. A generic visual-inertial registration framework is proposed here to estimate the drift-free rotational and translational pose of the underwater vehicle that can be directly fed to the high level vehicle controller. Underwater image formation model based image enhancement technique along with the pose estimation module is the key of the proposed G-VINS algorithm. The theoretical formulation along with the experimental results shows the robustness and the applicability of the proposed method in marine environment characterized by different level of turbidity.

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KW - pose estimation

KW - visual-inertial registration

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M3 - Conference contribution

AN - SCOPUS:85145779081

T3 - Oceans Conference Record (IEEE)

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ER -

Multisensor fusion for marine infrastructures' inspection and safety

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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