A Fuzzy Cooperative Localisation Framework for Underwater Robotic Swarms

Sabra, Adham ORCID: 0000-0003-1484-1399 and Fung, Wai-keung
(2020) A Fuzzy Cooperative Localisation Framework for Underwater Robotic Swarms. Sensors, 20 (19). E5496-.

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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. View Full-Text

Item Type: Article
Uncontrolled Keywords: underwater wireless sensor networks, underwater swarm robotics, autonomous underwater vehicles, underwater localisation, cooperative navigation, fuzzy systems
Depositing User: Symplectic Admin
Date Deposited: 15 Dec 2020 09:53
Last Modified: 18 Jan 2023 23:18
DOI: 10.3390/s20195496
Open Access URL: https://www.mdpi.com/1424-8220/20/19/5496
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3110110