A Fuzzy Cooperative Localisation Framework for Underwater Robotic Swarms
journal contributionposted on 18.02.2022, 15:56 by 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.
Cardiff Metropolitan University (Grant ID: Cardiff Metropolian (Internal)) This research was funded in part by The Oil and Gas Technology Centre, 20 Queens Road, Aberdeen, AB15 4ZT, Scotland; and Autonomous Robotics Ltd, Eastleigh Court, Bishopstrow, Warminster, BA12 9HW, England. The PhD scholarship of Adham Sabra was funded by the School of Engineering at Robert Gordon University in Aberdeen.
VersionVoR (Version of Record)
CitationSabra, A.; Fung, W.-K. A Fuzzy Cooperative Localisation Framework for Underwater Robotic Swarms. Sensors 2020, 20, 5496.
Cardiff Met Affiliation
- Cardiff School of Technologies