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A fuzzy cooperative localisation framework for underwater robotic swarms.

Sabra, Adham; Fung, Wai-Keung


Adham Sabra

Wai-Keung Fung


This article proposes a holistic localisation framework for underwater robotic swarms to dynamically fuse multiple position estimates of an autonomous underwater vehicle while using fuzzy decision support system. A number of underwater localisation methods have been proposed in the literature for wireless sensor networks. The proposed navigation framework harnesses the established localisation methods in order to provide navigation aids in the absence of acoustic exteroceptive sensors navigation aid (i.e., ultra-short base line) and it can be extended to accommodate newly developed localisation methods by expanding the fuzzy rule base. Simplicity, flexibility, and scalability are the main three advantages that are inherent in the proposed localisation framework when compared to other traditional and commonly adopted underwater localisation methods, such as the Extended Kalman Filter. A physics-based simulation platform that considers environment’s hydrodynamics, industrial grade inertial measurement unit, and underwater acoustic communications characteristics is implemented in order to validate the proposed localisation framework on a swarm size of 150 autonomous underwater vehicles. The proposed fuzzy-based localisation algorithm improves the entire swarm mean localisation error and standard deviation by 16.53% and 35.17%, respectively, when compared to the Extended Kalman Filter based localisation with round-robin scheduling.


SABRA, A. and FUNG, W.-K. 2020. A fuzzy cooperative localisation framework for underwater robotic swarms. Sensors [online], 20(19), article ID 5496. Available from:

Journal Article Type Article
Acceptance Date Sep 20, 2020
Online Publication Date Sep 25, 2020
Publication Date Oct 1, 2020
Deposit Date Oct 9, 2020
Publicly Available Date Oct 9, 2020
Journal Sensors
Print ISSN 1424-3210
Electronic ISSN 1424-8220
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 20
Issue 19
Article Number 5496
Keywords Electrical and Electronic Engineering; Analytical Chemistry; Atomic and Molecular Physics, and Optics; Biochemistry
Public URL


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