Ship hull inspection using a swarm of autonomous underwater robots: a Search algorithm

HAIRE, Matthew, XU, Xu, ALBOUL, Lyuba, PENDERS, Jacques and ZHANG, Hongwei (2019). Ship hull inspection using a swarm of autonomous underwater robots: a Search algorithm. 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).

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Official URL: https://ieeexplore.ieee.org/document/8848963
Link to published version:: https://doi.org/10.1109/SSRR.2019.8848963

Abstract

Emergency ship hull repair is a vital damage control procedure that makes the difference between reaching the next port and losing a ship. For repairs to be made, ship hull breaches must be quickly located and patched. In this paper, we propose a searching algorithm to be used by a homogeneous swarm of autonomous underwater robots to inspect a ship hull and identify breaches. Inspired by methods tested in 2D environments, we combine aspects of previous studies and implement them in a 3D environment. We compare two approaches designed to achieve complete area coverage of a large section of ship hull and identify the approach that yields the shortest discovery time and highest accuracy. Our system is verified within the Webots software simulated environment and shows that the system is resilient to sensor noise and failure of a fraction of the robot population.

Item Type: Article
Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. SSRR 2019 (IEEE International Symposium On Safety, Security And Rescue Robotics)Wurzburg, Germany 2 Sep 2019 - 4 Sep 2019
Identification Number: https://doi.org/10.1109/SSRR.2019.8848963
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 23 Sep 2019 13:41
Last Modified: 18 Mar 2021 03:06
URI: https://shura.shu.ac.uk/id/eprint/25170

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